Interviewing is one of the most common techniques used to conduct qualitative research in the social sciences and humanities. As a result of globalization, researchers increasingly conduct interviews cross-, inter- and intra-nationally. This raises important questions about how differences and sameness are understood and negotiated within the interview situation, as well as the power structures at play within qualitative research, and the role that reflexivity plays in mediating these. What does it mean to interview Black women as a Black woman? How is ethnicity negotiated across various qualitative research encounters? How are differences bridged or asserted in feminist interviewing? These are just some of the questions explored in the chapters in this volume. Drawing on their recent research, the contributors detail their experiences of engaging in qualitative interviewing and examine how they negotiated the various dilemmas they encountered. The contributions challenge some of the assumptions made in early feminist work on interviewing, providing nuanced accounts of actual research experiences. This volume explores the practice and implications of conducting cross-, inter- and intra-cultural interviewing, bringing together researchers from a range of disciplines and countries to describe and analyse both its vicissitudes and its advantages.

A high-level, informal look at the different stages of the predictive analytics cycle Understanding the Predictive Analytics Lifecycle covers each phase of the development of a predictive analytics initiative. Through the use of illuminating case studies across a range of industries that include banking, megaresorts, mobile operators, healthcare, manufacturing, and retail, the book successfully illustrates each phase of the predictive analytics cycle to create a playbook for future projects. Predictive business analytics involves a wide variety of inputs that include individuals' skills, technologies, tools, and processes. To create a successful analytics program or project to gain forward-looking insight into making business decisions and actions, all of these factors must properly align. The book focuses on developing new insights and understanding business performance based on extensive use of data, statistical and quantitative analysis, explanatory and predictive modeling, and fact-based management as input for human decisions. The book includes: An overview of all relevant phases: design, prepare, explore, model, communicate, and measure Coverage of the stages of the predictive analytics cycle across different industries and countries A chapter dedicated to each of the phases of the development of a predictive initiative A comprehensive overview of the entire analytic process lifecycle If you're an executive looking to understand the predictive analytics lifecycle, this is a must-read resource and reference guide.