- ホーム
- > 洋書
- > 英文書
- > Business / Economics
Full Description
Researching and Analysing Business: Research Methods in Practice provides an accessible and practical guide to various data collection and data analysis techniques within management, from both quantitative and qualitative perspectives.
This key resource functions as a comprehensive reference tool - covering a broad variety of methodologies - examining both the theory behind them and their application in practice. These include systematic literature review through bibliometric and meta-analysis, secondary vs primary sources, qualitative research vs quantitative research, combining qualitative and quantitative methods, qualitative and quantitative research method approaches, fsQCA, data mining, and sentiment analysis. Chapters are rich in examples, data sets, practical exercises, easy-to-follow slides, and a glossary, which help readers to understand and apply research approaches as well as to assess the strengths and weaknesses of each method.
Unique in its practical approach and with insights from active researchers, this book is required and recommended reading for advanced undergraduate and postgraduate students studying research methods as a core module within business and management courses. It is also a useful tool for PhD students and academics within the discipline.
Online support materials include PowerPoint slides.
Contents
Chapter 1. Introduction: Research Methods in Business and Management: Theoretical and Practical Perspectives. Chapter 2. Mixed-methods approach: Combining qualitative & quantitative methods. Part 1 - SYSTEMATIC LITERATURE REVIEW. Chapter 3. Bibliometric Analysis: Main procedure and guidelines. Chapter 4. Systematic literature review: main procedures and guidelines for interpreting the results. Part 2 - QUALITATIVE. Chapter 5. Grounded Theory: What, Why and How. Chapter 6. Applying Netnographic Approach to Qualitative Research. Chapter 7. Qualitative approaches: Case study research. Chapter 8. Conducting qualitative management research with semi-structured interviews: From planning to interpretation. Chapter 9. Qualitative Data Analysis: Using Thematic Analysis. Chapter 10. Qualitative Data Analysis: Using NVivo. Chapter 11. Text Mining and Topic Modelling. Chapter 12. Delphi method - A practical guide for verifying and validating novel developments. Chapter 13. Eye-Tracking: collecting data; managing, and process, analysis and interpretation. Chapter 14. Semiotic analysis in financial markets. Chapter 15. Critical Discourse Analysis. Chapter 16. Qualitative research methods to capture emerging visual social media culture. Chapter 17. Online data analysis: Sentiment analysis with Python. Part 3 - QUANTITATIVE. Chapter 18. Non-response bias & common method bias in survey research. Chapter 19. Scale Formation: Scale Reliability Analysis and Exploratory Factor Analysis. Chapter 20. Partial Least Squares Structural Equation Modeling: A Nontechnical and Practical Guide. Chapter 21. Addressing endogeneity in survey research: Application of two-stage least squares (2SLS) regression analysis. Chapter 22. Big Data in Marketing Intelligence. Chapter 23. Panel Data and Accounting context. Chapter 24. Fuzzy-Set Qualitative Comparative Analysis: Introduction to a Configurational Approach. Chapter 25. Title: Fuzzy Analytic hierarchy Process: A Simplified Approach. Chapter 26. Quantitative research with R programming language used in Marketing Research.
