Front Matter; Copyright; Contents; List of figures; List of tables and boxes; About the editors; List of contributors; 1 Qualitative research in HRM: innovation over stagnation; PART I: DESIGNING QUALITATIVE PROJECTS; 2 The role of qualitative methods in mixed methods designs; 3 Anchoring qualitative methods for longitudinal studies; 4 Autoethnography: a novel way to study HRM; PART II: INNOVATIONS IN DATA SOURCES; 5 Using legal research methods in human resource management research; 6 The use of news media as a data source in HRM research: exploring society's perceptions 7 Netnographical methods and the challenge of researching hidden and secretive employee social media practices8 Doing historical research in human resource management: with some reflections on an academic career; 9 Thinking about philosophical methods in human resources; PART III: INNOVATIONS IN DATA COLLECTION METHODS; 10 An experiment with "the miracle question": an innovative data collection technique in HR research; 11 Using photo-elicitation to understand experiences of work-life balance 12 Using qualitative repertory grid interviews to gather shared perspectives in a sequential mixed methods research design13 Free verbal associations: measuring what people think about employee participation; 14 Using qualitative diaries to uncover the complexities of daily experiences; 15 Autoethnographic vignettes in HRM; PART IV: INNOVATIVE DATA ANALYSIS; 16 Computer-supported qualitative research; 17 Cross-cultural HRM research: the potential of causal cognitive mapping; 18 Deriving behavioural role descriptions from the perspectives of job-holders: an illustrative example; Index.

This Handbook explores the opportunities and challenges of new technologies for innovating data collection and data analysis in the context of human resource management. Written by some of the world's leading researchers in their field, it comprehensively explores modern qualitative research methods from good project design, to innovations in data sources and data collection methods and, finally, to best-practice in data analysis.