This book synthesizes a decade of research by the author into fundamental issues in organization design. The result is a novel micro-structural perspective on organizations, which aims to both expand and narrow current thinking. The new perspective takes an expansive view on the kinds of phenomena that can be studied in terms of organization design- such as cross-functional teams, strategic partnerships, buyer-supplier relations, alliance networks, mega-projects, post-merger integration, business groups, open source communities, and crowdsourcing, besides traditional concerns with bureaucratic organizations. At the same time, this approach narrows focus by abstracting away from the variety and complexity of organizations to a few fundamental and universal problems of organizing (that relate to how they aggregate their members' efforts), as well as a few reusable building blocks microstructures (which capture common patterns of interaction between members of an organization). The microstructural approach to organizations will be of interest to researchers and PhD students in management, organization science, and strategy.
Rapid access to information is a prime requirement in any organization that wants to have a competitive edge in today's fast changing markets. How to retrieve information? How to capture data? How to format it? The answer lies in Data Warehousing. This HOTT Guide will give you access to all the essential information about the newest data storehouse: through articles by expert trendwachters on strategic considerations, how-to reports defining the various ways to extract the data needed for critical business decisions, technical papers clarifying technologies and tools, business cases and key concepts that will provide the reader with a comprehensive overview of a business solution that is already indispensable.
Theories of Small Groups: Interdisciplinary Perspectives brings together the threads that unify the field of group research. The book is designed to define and describe theoretical perspectives on groups and to highlight select research findings within those perspectives. In this text, editors Marshall Scott Poole and Andrea B. Hollingshead capitalize on the theoretical advances made over the last fifty years by integrating models and theories of small groups into a set of nine general theoretical perspectives. Theories of Small Groups is the first book to assess, synthesize, integrate, and evaluate the body of theory and research on small groups across disciplinary boundaries.
Compliance with federal equal employment opportunity regulations, including civil rights laws and affirmative action requirements, requires collection and analysis of data on disparities in employment outcomes, often referred to as adverse impact. While most human resources (HR) practitioners are familiar with basic adverse impact analysis, the courts and regulatory agencies are increasingly relying on more sophisticated methods to assess disparities. Employment data are often complicated, and can include a broad array of employment actions (e.g., selection, pay, promotion, termination), as well as data that span multiple protected groups, settings, and points in time. In the era of "big data," the HR analyst often has access to larger and more complex data sets relevant to employment disparities. Consequently, an informed HR practitioner needs a richer understanding of the issues and methods for conducting disparity analyses. This book brings together the diverse literature on disparity analysis, spanning work from statistics, industrial/organizational psychology, human resource management, labor economics, and law, to provide a comprehensive and integrated summary of current best practices in the field. Throughout, the description of methods is grounded in the legal context and current trends in employment litigation and the practices of federal regulatory agencies. The book provides guidance on all phases of disparity analysis, including: How to structure diverse and complex employment data for disparity analysis How to conduct both basic and advanced statistical analyses on employment outcomes related to employee selection, promotion, compensation, termination, and other employment outcomes How to interpret results in terms of both practical and statistical significance Common practical challenges and pitfalls in disparity analysis and strategies to deal with these issues
The dramatic increase in global trade confronts service firms with the challenge of adapting their services to the varying requirements of customers in different cultures. Jan H. Schumann focuses on three relationship marketing issues that are of relevance for both academics and practitioners: the establishment of trusting customer relationships, customer co-production, and the effect of word-of-mouth referrals.
The shifting influence of growing organizational cultures and individual standards has caused significant changes to modern organizations. By creating a better understanding of these influences, the quality of organizations can be improved. Exploring the Influence of Personal Values and Cultures in the Workplace is a pivotal reference source for the latest research on how culture and personal values shape and influence employees’ actions, behaviors, and leadership styles. Featuring extensive coverage on relevant areas such as psychological health, career management, and job satisfaction, this publication is an ideal resource for practitioners, professionals, managers, and researchers seeking innovative perspectives on the impact of personal values and cultures in the workplace.
Tackling the question of how to effectively aggregate uncertain preference information in multiple structures given by decision-making groups, Theory and Approaches of Unascertained Group Decision-Making focuses on group aggregation methods based on uncertainty preference information. It expresses the complexity existing in each group decision-maki
Key features: Unique in its combination of serving as an introduction to spatial statistics and to modeling agricultural and ecological data using R Provides exercises in each chapter to facilitate the book's use as a course textbook or for self-study Adds new material on generalized additive models, point pattern analysis, and new methods of Bayesian analysis of spatial data. Includes a completely revised chapter on the analysis of spatiotemporal data featuring recently introduced software and methods Updates its coverage of R software including newly introduced packages Spatial Data Analysis in Ecology and Agriculture Using R, 2nd Edition provides practical instruction on the use of the R programming language to analyze spatial data arising from research in ecology, agriculture, and environmental science. Readers have praised the book's practical coverage of spatial statistics, real-world examples, and user-friendly approach in presenting and explaining R code, aspects maintained in this update. Using data sets from cultivated and uncultivated ecosystems, the book guides the reader through the analysis of each data set, including setting research objectives, designing the sampling plan, data quality control, exploratory and confirmatory data analysis, and drawing scientific conclusions. Additional material to accompany the book, on both analyzing satellite data and on multivariate analysis, can be accessed at https://www.plantsciences.ucdavis.edu/plant/additionaltopics.htm.