This book is about increasing team performance. It focuses on building system dynamics models when tackling a mix of interrelated strategic problems to enhance team learning, foster consensus, and create commitment. The book is intended to be applied in the organizations of today. As the "command and control" organization evolves into one of decision-making teams, so these teams have become the critical building blocks upon which the performance of the organization depends. The team members face an increased complexity of decision making with the interrelation of several strategic problems. What this means is that people have different views of the situation and will define problems differently. However, research shows that this can in fact be very productive if and when people learn from each other in order to build a shared perspective. Learning in this way might prove to be the only sustainable competitive advantage for organizations in the future. As a result, team leaders want to create "learning teams" and are confronted with issues such as how to: create a situation where people doubt their ideas rather than stubbornly cling to dearly held views create a learning atmosphere rather than trying to "win" the discussion create a shared understanding of a problem in a team foster consensus and create commitment with a strategic decision facilitate Group Model Building Those who will benefit most from Group Model Building: Facilitating Team Learning Using System Dynamics are those who are familiar with systems thinking or organizational learning, or those who are working in groups and are coming up against the common difficulties.

Community Based System Dynamics introduces researchers and practitioners to the design and application of participatory systems modeling with diverse communities. The book bridges community- based participatory research methods and rigorous computational modeling approaches to understanding communities as complex systems. It emphasizes the importance of community involvement both to understand the underlying system and to aid in implementation. Comprehensive in its scope, the volume includes topics that span the entire process of participatory systems modeling, from the initial engagement and conceptualization of community issues to model building, analysis, and project evaluation. Community Based System Dynamics is a highly valuable resource for anyone interested in helping to advance social justice using system dynamics, community involvement, and group model building, and helping to make communities a better place.

Learn how to use R to turn raw data into insight, knowledge, and understanding. This book introduces you to R, RStudio, and the tidyverse, a collection of R packages designed to work together to make data science fast, fluent, and fun. Suitable for readers with no previous programming experience, R for Data Science is designed to get you doing data science as quickly as possible. Authors Hadley Wickham and Garrett Grolemund guide you through the steps of importing, wrangling, exploring, and modeling your data and communicating the results. You'll get a complete, big-picture understanding of the data science cycle, along with basic tools you need to manage the details. Each section of the book is paired with exercises to help you practice what you've learned along the way. You'll learn how to: Wrangle—transform your datasets into a form convenient for analysis Program—learn powerful R tools for solving data problems with greater clarity and ease Explore—examine your data, generate hypotheses, and quickly test them Model—provide a low-dimensional summary that captures true "signals" in your dataset Communicate—learn R Markdown for integrating prose, code, and results

Published in 1997, this study focused on building and empirically validating a model of family centred group care. This is an alternative to the traditional model of group child care that is primarily child centred and which reflects the notion of group care as a substitute for parental care. The model represents a step forward in the conceptualization of group care practice as both child centred and family affirming. The Family Centred Group Care instrument used in the study is unique in that this is the first to measure a model of group care empirically. The book will be of interest to child welfare practitioners, social workers, child care workers and other human service personnel as well as managers of agencies that provide group care services for children and at-risk youth. Researchers and policy makers will also find this book useful as the study advances the application of empirical methodology to human service programs.

Effective software teams are essential for any organization to deliver value continuously and sustainably. But how do you build the best team organization for your specific goals, culture, and needs? Team Topologies is a practical, step-by-step, adaptive model for organizational design and team interaction based on four fundamental team types and three team interaction patterns. It is a model that treats teams as the fundamental means of delivery, where team structures and communication pathways are able to evolve with technological and organizational maturity. In Team Topologies, IT consultants Matthew Skelton and Manuel Pais share secrets of successful team patterns and interactions to help readers choose and evolve the right team patterns for their organization, making sure to keep the software healthy and optimize value streams. Team Topologies is a major step forward in organizational design for software, presenting a well-defined way for teams to interact and interrelate that helps make the resulting software architecture clearer and more sustainable, turning inter-team problems into valuable signals for the self-steering organization.

Publication of the Handbook of Group Decision and Negotiation marks a milestone in the evolution of the group decision and negotiation (GDN) eld. On this occasion, editors Colin Eden and Marc Kilgour asked me to write a brief history of the eld to provide background and context for the volume. They said that I am in a good position to do so: Actively involved in creating the GDN Section and serving as its chair; founding and leading the GDN journal, Group Decision and Negotiation as editor-in-chief, and the book series, “Advances in Group Decision and Negotiation” as editor; and serving as general chair of the GDN annual meetings. I accepted their invitation to write a brief history. In 1989 what is now the Institute for Operations Research and the Management Sciences (INFORMS) established its Section on Group Decision and Negotiation. The journal Group Decision and Negotiation was founded in 1992, published by Springer in cooperation with INFORMS and the GDN Section. In 2003, as an ext- sion of the journal, the Springer book series, “Advances in Group Decision and Negotiation” was inaugurated.

Governments play a major role in the development process, and constantly introduce reforms and policies to achieve developmental objectives. Many of these interventions have limited impact, however; schools get built but children don't learn, IT systems are introduced but not used, plans are written but not implemented. These achievement deficiencies reveal gaps in capabilities, and weaknesses in the process of building state capability. This book addresses these weaknesses and gaps. It starts by providing evidence of the capability shortfalls that currently exist in many countries, showing that many governments lack basic capacities even after decades of reforms and capacity building efforts. The book then analyses this evidence, identifying capability traps that hold many governments back - particularly related to isomorphic mimicry (where governments copy best practice solutions from other countries that make them look more capable even if they are not more capable) and premature load bearing (where governments adopt new mechanisms that they cannot actually make work, given weak extant capacities). The book then describes a process that governments can use to escape these capability traps. Called PDIA (problem driven iterative adaptation), this process empowers people working in governments to find and fit solutions to the problems they face. The discussion about this process is structured in a practical manner so that readers can actually apply tools and ideas to the capability challenges they face in their own contexts. These applications will help readers devise policies and reforms that have more impact than those of the past.

This book has been replaced by Principles and Practice of Structural Equation Modeling, Fifth Edition, ISBN 978-1-4625-5191-0.

This book is the first practical, hands-on guide that shows how leaders can build psychological safety in their organizations, creating an environment where employees feel included, fully engaged, and encouraged to contribute their best efforts and ideas. Fear has a profoundly negative impact on engagement, learning efficacy, productivity, and innovation, but until now there has been a lack of practical information on how to make employees feel safe about speaking up and contributing. Timothy Clark, a social scientist and an organizational consultant, provides a framework to move people through successive stages of psychological safety. The first stage is member safety-the team accepts you and grants you shared identity. Learner safety, the second stage, indicates that you feel safe to ask questions, experiment, and even make mistakes. Next is the third stage of contributor safety, where you feel comfortable participating as an active and full-fledged member of the team. Finally, the fourth stage of challenger safety allows you to take on the status quo without repercussion, reprisal, or the risk of tarnishing your personal standing and reputation. This is a blueprint for how any leader can build positive, supportive, and encouraging cultures in any setting.

Praise for Bayes Rules!: An Introduction to Applied Bayesian Modeling “A thoughtful and entertaining book, and a great way to get started with Bayesian analysis.” Andrew Gelman, Columbia University “The examples are modern, and even many frequentist intro books ignore important topics (like the great p-value debate) that the authors address. The focus on simulation for understanding is excellent.” Amy Herring, Duke University “I sincerely believe that a generation of students will cite this book as inspiration for their use of – and love for – Bayesian statistics. The narrative holds the reader’s attention and flows naturally – almost conversationally. Put simply, this is perhaps the most engaging introductory statistics textbook I have ever read. [It] is a natural choice for an introductory undergraduate course in applied Bayesian statistics." Yue Jiang, Duke University “This is by far the best book I’ve seen on how to (and how to teach students to) do Bayesian modeling and understand the underlying mathematics and computation. The authors build intuition and scaffold ideas expertly, using interesting real case studies, insightful graphics, and clear explanations. The scope of this book is vast – from basic building blocks to hierarchical modeling, but the authors’ thoughtful organization allows the reader to navigate this journey smoothly. And impressively, by the end of the book, one can run sophisticated Bayesian models and actually understand the whys, whats, and hows.” Paul Roback, St. Olaf College “The authors provide a compelling, integrated, accessible, and non-religious introduction to statistical modeling using a Bayesian approach. They outline a principled approach that features computational implementations and model assessment with ethical implications interwoven throughout. Students and instructors will find the conceptual and computational exercises to be fresh and engaging.” Nicholas Horton, Amherst College An engaging, sophisticated, and fun introduction to the field of Bayesian statistics, Bayes Rules!: An Introduction to Applied Bayesian Modeling brings the power of modern Bayesian thinking, modeling, and computing to a broad audience. In particular, the book is an ideal resource for advanced undergraduate statistics students and practitioners with comparable experience. Bayes Rules! empowers readers to weave Bayesian approaches into their everyday practice. Discussions and applications are data driven. A natural progression from fundamental to multivariable, hierarchical models emphasizes a practical and generalizable model building process. The evaluation of these Bayesian models reflects the fact that a data analysis does not exist in a vacuum. Features • Utilizes data-driven examples and exercises. • Emphasizes the iterative model building and evaluation process. • Surveys an interconnected range of multivariable regression and classification models. • Presents fundamental Markov chain Monte Carlo simulation. • Integrates R code, including RStan modeling tools and the bayesrules package. • Encourages readers to tap into their intuition and learn by doing. • Provides a friendly and inclusive introduction to technical Bayesian concepts. • Supports Bayesian applications with foundational Bayesian theory.