Business Research Methodology is a comprehensive, student-centric, and visually rich textbook that transforms how students learn research methods. Designed exactly as per the NEP-aligned syllabus for DSE 6.6/7.1 of B.Com. (Hons.) and B.Com., the book approaches research not as a theoretical subject, but as a step-by-step journey of discovery, supported by real datasets, SPSS screenshots, spreadsheet methods, case studies, solved examples, numerical exercises, and practical tasks. The authors break down the entire research process into five structured units, starting from the very basics—what research is and how it is shaped by philosophy—and progressing toward data analysis, inferential statistics, report writing, and ethical concerns. Every chapter is carefully designed to help students understand, apply, practise, and eventually master business research. The book stands out because it does not stop at theory. It teaches students how research is actually done, using tools they will encounter in business analytics—SPSS software, spreadsheets, structured datasets, and contemporary research practices. The seamless integration of conceptual clarity and practical exposure makes it suitable not only for university exams but also for dissertation writing, research internships, and early-stage research careers.

This book is intended for the following audience:

• B.Com. (Hons.) and B.Com. Students studying the NEP-based DSE 6.6/7.1 paper
• Postgraduate Commerce & Management Students undertaking dissertations or major projects
• Research Beginners, Interns & Early-Stage Scholars needing structured guidance
• UPSC/State PSC Aspirants working on research aptitude, statistics, or project components
• Faculty Members who want a classroom-ready, activity-based, outcomes-oriented textbook
• Students working on live projects, field surveys, primary data collection, or report writing

The Present Publication is the Latest Edition, authored by Prof. (Dr) Pushpender Kumar and Dr Anupreet Kaur Mokha, with the following noteworthy features:

• [Complete Coverage of the Research Cycle] The book walks students through every stage of business research, beginning with core concepts and philosophical approaches, progressing through design, sampling, data collection, analysis, and culminating in professional report writing. It ensures that learners understand not only what each stage involves but also how to execute it in real academic and business settings
• [Highly Practice-driven]  Each analytical topic is paired with hands-on exercises using SPSS and spreadsheets. Students follow clear procedures, view actual software outputs, and work with real datasets provided in the appendix. This enables them to turn theoretical understanding into practical analytical skills
• [Detailed Visuals] The book simplifies complex topics through a variety of visual aids. From sampling frameworks and research models to data presentation charts and scaling classifications, visuals help students quickly grasp and retain key ideas.
• [Strong Conceptual Clarity] Definitions, distinctions, lists, and structured frameworks appear throughout the text. Concepts such as research types, levels of measurement, reliability/validity, and sampling methods are presented in clear, comparative tables that make learning systematic and accessible.
• [Case Study Integration] Every chapter closes with a case study that illustrates how concepts apply in live business environments—consumer behaviour, HR analytics, financial decisions, and more. This reinforces learning through practical relevance
• [Ethics-focused] A full chapter addresses ethical concerns in research design, data collection, respondent rights, analysis, and reporting. Students develop the ethical sensitivity expected of academic researchers and corporate analysts.
• [Student-friendly Design] Each chapter includes summaries, MCQs, short and long answer questions, numericals, and practical tasks. This structure supports revision, classroom discussion, project work, and exam preparation
• [Alignment with NEP Learning Outcomes] The book’s pedagogy emphasises hands-on work, problem-solving, application through software tools, and conceptual understanding—directly reflecting NEP’s focus on skill-based, activity-driven, and experiential education
• [Exam-ready Content] With solved examples, thorough assessments, and actual university question papers, students gain a clear idea of exam patterns and expectations, making the book an effective preparation tool for internal assessments and final examinations

The coverage of the book is as follows:

• Introduction to Research – Builds a strong conceptual foundation:
  • Meaning, scope, and significance of research
  • Research terminologies (concepts, variables, constructs, hypotheses, models, theories)
  • Types of Research – Quantitative/qualitative, conceptual/empirical, fundamental/applied, cross-sectional/longitudinal
  • Philosophical approaches (positivism, interpretivism, pragmatism)
  • Deductive vs Inductive reasoning with frameworks and visuals
  • Research Process – Step-by-step explanation
  • How to conduct a literature review (steps, sources, synthesis)
  • How to formulate research questions, with examples and common mistakes
• Research Design – Provides a blueprint for conducting research:
  • Meaning and characteristics of research design
  • Exploratory, descriptive, and experimental designs
  • When and how each design is used in business studies
  • Examples and structured diagrams to choose appropriate designs
• Data Collection – A comprehensive and application-rich unit:
  • Measurement & Scaling
    • Levels of measurement (nominal, ordinal, interval, ratio)
    • Comparative scales (ranking), non-comparative scales (rating)
    • Likert, semantic differential, Stapel scales
    • Reliability & validity (types, measurement, examples)
  • Survey Methods
    • Types of Surveys – Online, telephonic, personal, mail-based
    • Characteristics of a good survey
    • Designing questionnaires, respondent bias, and pilot testing
  • Sampling Techniques
    • Concepts – Population, sampling units, sampling frame
    • Probability Sampling – Random, stratified, systematic, cluster
    • Non-probability sampling: convenience, purposive, quota, judgmental
    • Sample size determination (logic, formulae, examples)
• Data Analysis using Spreadsheet & SPSS – Highly practical, tool-based, and skill-building:
  • Data Preparation & Cleaning
    • Handling missing values
    • Detecting outliers
    • Coding/recoding variables
    • Classification of data
    • Visual Presentation – Tables, line charts, bar charts, pie charts, histograms, box plots
  • Descriptive Statistics
    • Measures of central tendency (mean, median, mode)
    • Measures of variation (range, IQR, variance, SD, coefficient of variation)
    • Skewness, kurtosis, interpretation with visuals
  • Inferential Statistics (with SPSS & Spreadsheet Procedures) – Each test includes a practical example, SPSS steps, spreadsheet method & output interpretation:
    • One-sample Z-test & Two-sample Z-test
    • One-sample t-test
    • Paired-sample t-test
    • Independent-sample t-test
    • Chi-square tests (goodness of fit & independence)
    • Non-parametric tests:
      • Kolmogorov–Smirnov
      • Mann–Whitney U
      • Kruskal–Wallis
      • Median test
      • Sign test
      • McNemar test
    • Also includes numerical questions and practical exercises for every major concept
• Report Writing & Ethics – Focuses on academic writing and responsible research practices:
  • Types of reports (contractual, project, research, evaluation, annual)
  • Structure of a well-written research report
  • Referencing and bibliography (with examples)
  • Format and presentation guidelines (tables, figures, layout)
  • Ethical issues at each research stage
  • Rights and responsibilities of researchers, sponsors, and respondents

Each chapter follows a consistent and reader-friendly design:

• Clear learning objectives
• Introductory examples for context
• Step-by-step explanations with flowcharts and diagrams
• Tables contrasting key concepts
• SPSS and Spreadsheet tutorials
• Rich visuals for data presentation and theory models
• Case study to encourage application
• Summary for quick revision
• MCQs, short & long answer questions
• Numerical questions and practical tasks for skill-building
• The progression ensures that students first gain conceptual clarity, then immerse themselves in application.