28:02

S01:E13 May 20, 2025

Chapter 13: Unobtrusive Research

This podcast explores unobtrusive research methods, which involve gathering information without directly interacting with the people being studied. The hosts explain how these techniques allow researchers to examine the “traces” people leave behind, providing insights that might not emerge through direct questioning. The conversation covers three main approaches: content analysis (systematically examining texts and media), analyzing physical traces and artifacts (studying tangible objects people create or leave behind), and using existing data collected by others. The hosts discuss the strengths of unobtrusive methods, including eliminating reactivity bias, cost-effectiveness, and the ability to study historical trends or sensitive topics. The episode addresses how digital technology has revolutionized unobtrusive research through social media analysis, digital ethnography, and big data. The hosts explain techniques for ensuring reliability and validity when using these methods and discuss how combining unobtrusive approaches with other methods like surveys or interviews can provide more comprehensive understanding. Throughout, they use concrete examples to illustrate how these detective-like approaches reveal patterns in human behavior. This podcast was generated using NotebookLM.

28:00

S01:E12 May 20, 2025

Chapter 12: Field Research

This podcast explores field research, where researchers study people in their natural settings rather than laboratory environments. The hosts begin with sociologist Arlie Hochschild’s work on household chore division to illustrate how direct observation can reveal discrepancies between what people say they do and what they actually do. The conversation explains participant observation as a spectrum from complete outsider to fully integrated member of the group being studied. The hosts discuss the balancing act researchers face between gaining insider understanding and maintaining analytical distance, emphasizing the importance of reflexivity (self-awareness of biases). They trace field research’s roots from anthropology to urban sociology through examples like William Foote White’s “Street Corner Society” and Alice Goffman’s “On the Run.” The episode covers practical aspects including site selection, gaining access, ethical considerations, detailed field note-taking, and analysis techniques. The hosts distinguish between descriptive notes (objective observations) and analytic notes (interpretations and reflections), explaining how these form the foundation for identifying patterns and developing theory from firsthand experiences. This podcast was generated using NotebookLM.

27:03

S01:E11 May 20, 2025

Chapter 11: Interview Research

This podcast explores interview research as a powerful method for uncovering the “why” behind human behavior and opinions. The hosts reference sociologist Michael Kimmel’s work interviewing 400 young men to illustrate how in-depth conversations can reveal insights that statistics alone might miss. The conversation distinguishes between qualitative interviews (flexible, semi-structured for depth) and quantitative interviews (highly standardized for statistical analysis). The hosts explain the interviewer’s critical role in preparation, building rapport, motivating participants, and ensuring quality data collection. They provide practical guidance on creating effective interview guides, asking good questions, and conducting interviews ethically. The episode addresses important considerations like location, power dynamics, and researcher reflexivity, along with practical challenges such as recording, transcription, and coding for analysis. The hosts discuss how focus groups differ from one-on-one interviews and how technology is changing interview methods. Throughout, they emphasize that interviewing is both a science and an art requiring systematic approach combined with interpersonal sensitivity. This podcast was generated using NotebookLM.

36:09

S01:E10 May 20, 2025

Chapter 10: Inferential Statistics

This podcast explores how researchers use statistics to transform raw data into meaningful insights. The hosts begin with a practical example of a bakery owner considering delivery options to illustrate how statistics help with real-world decision-making. They explain the progression from descriptive statistics (summarizing data) to inferential statistics (drawing broader conclusions from samples). The conversation covers measures of central tendency (mean, median, mode) and variability (range, variance, standard deviation), explaining when each is most appropriate. The hosts walk through the hypothesis testing process, clarifying concepts like null and alternative hypotheses, significance levels, p-values, and confidence intervals while emphasizing their proper interpretation and limitations. The episode distinguishes between parametric tests (t-tests, ANOVA, correlation) and non-parametric alternatives (Mann-Whitney U, Kruskal-Wallis, Spearman’s rank), explaining when each is appropriate based on data characteristics and research questions. The hosts stress the importance of effect sizes alongside statistical significance and advocate for comprehensive reporting of statistical results with appropriate context. This podcast was generated using NotebookLM.

30:30

S01:E09 May 20, 2025

Chapter 9: Experimental Research

This podcast explores experimental research as the gold standard for establishing cause-and-effect relationships. The hosts explain that experiments involve deliberately manipulating variables while controlling other factors, allowing researchers to confidently determine if specific changes cause particular outcomes. The conversation distinguishes between laboratory experiments (highly controlled but potentially artificial) and field experiments (more natural but with less control). The hosts outline the essential components of experiments including treatment and control groups, manipulation of independent variables, measurements before and after intervention, and random assignment to conditions. The episode covers various experimental designs including basic two-group experiments, factorial designs for testing multiple factors, and hybrid designs like randomized block and Solomon four-group. The hosts also discuss quasi-experiments (lacking random assignment) such as regression discontinuity and non-equivalent group designs, explaining their applications and limitations. Throughout, they use real-world examples from fields like marketing, education, and psychology to illustrate abstract concepts. This podcast was generated using NotebookLM.

37:27

S01:E08 May 20, 2025

Chapter 8: Survey Research

This podcast examines survey research as a powerful tool for gathering information directly from people. The hosts discuss how surveys can measure things that can’t be directly observed, such as preferences, attitudes, beliefs, and self-reported behaviors, while noting their limitations including potential biases in responses. The conversation distinguishes between cross-sectional surveys (capturing a specific moment) and different types of longitudinal surveys (trend, panel, cohort, and retrospective), each offering unique insights into changes over time. The hosts cover various administration methods including printed questionnaires, group-administered surveys, and online surveys. The episode provides detailed guidance on designing effective questionnaires, covering question writing principles, response formats, logical ordering, and pretesting. The hosts address practical aspects like translation, incentives, and response rates, as well as ethical considerations and data analysis approaches. They emphasize the importance of understanding both the strengths and limitations of survey methods for gathering reliable information. This podcast was generated using NotebookLM.

27:10

S01:E07 May 20, 2025

Chapter 7: Sampling Methods

This podcast explores sampling, the process of selecting a subset of individuals to learn about a larger population. The hosts outline three critical stages of sampling: defining the target population (who you want to study), establishing a sampling frame (who you can actually reach), and selecting the actual sample using appropriate methods. The conversation distinguishes between probability sampling (where everyone has a known chance of selection) and non-probability sampling (where selection isn’t based on chance). The hosts describe specific probability techniques including simple random, systematic, stratified, cluster, matched pair, and multistage sampling, along with non-probability approaches like convenience, quota, snowball, purposive, and expert sampling. The episode addresses statistical concepts related to sampling including sampling distributions, confidence intervals, and determining appropriate sample sizes. The hosts emphasize that understanding how samples were selected is crucial for evaluating research findings, noting common biases that can undermine the value of research results. This podcast was generated using NotebookLM.

23:41

S01:E06 May 20, 2025

Chapter 6: Understanding Data

This podcast examines the fundamentals of data in research, distinguishing between raw data (unprocessed facts and observations) and information (processed, organized data with context). The hosts explore the two main types of data—qualitative (categorical) and quantitative (numerical)—and their various subtypes including nominal, ordinal, interval, and ratio data. The conversation covers different rating scales used in research such as binary, Likert, semantic differential, and Guttman scales, explaining how each captures different aspects of people’s opinions or behaviors. The hosts discuss the normal distribution (bell curve) and ways data can deviate from normality through skewness and kurtosis. The episode addresses practical aspects of working with data including database management, dealing with “dirty” or missing data, accessing public databases, choosing appropriate statistical tests, and using data mining techniques. The hosts use everyday examples like a bakery owner considering delivery options to illustrate abstract concepts in an accessible way. This podcast was generated using NotebookLM.

32:20

S01:E05 May 20, 2025

Chapter 5: Defining and Measuring Concepts

This podcast explores the critical process of measurement in research, comparing it to the precision needed in baking where exact measurements lead to predictable results. The hosts explain how researchers move through a systematic process of conceptualization (defining abstract ideas), operationalization (determining how to measure them), data collection, and analysis. The conversation distinguishes between directly observable variables and abstract constructs that require indirect measurement through indicators. The hosts explain different types of variables (independent, dependent, mediating, moderating, and control) and discuss how researchers evaluate measurement quality through reliability (consistency) and validity (accuracy). The episode covers both quantitative and qualitative approaches to measurement validation, presenting real-world research examples to illustrate these concepts. The hosts emphasize that good measurement is fundamental to all research, as even the most sophisticated analysis cannot overcome poor initial measurement. This podcast was generated using NotebookLM.

15:19

S01:E04 May 20, 2025

Chapter 4: Research Design

This podcast examines the essential process of creating an effective research design. The hosts begin by discussing how researchers must acknowledge their own perspectives before starting any project, emphasizing that recognizing personal biases is crucial for objective research. They explain the three main types of research: exploratory, descriptive, and explanatory. The conversation highlights the importance of crafting clear, focused research questions that are open-ended and allow for multiple potential answers. The hosts discuss how to develop testable hypotheses (predicted relationships between variables) and explain the difference between independent, dependent, and other variable types that form the foundation of research design. The episode covers feasibility considerations like access to participants, time constraints, resources, and technical expertise. The hosts use everyday examples to illustrate abstract concepts, making research design principles accessible to listeners with different backgrounds and experience levels. This podcast was generated using NotebookLM.

30:14

S01:E03 May 20, 2025

Chapter 3: Ethics in Research

This podcast explores the critical topic of research ethics, discussing how ethical considerations shape responsible research practices. The hosts define ethics as the moral principles governing behavior and explain how these principles become formalized in professional codes of conduct overseen by bodies like Institutional Review Boards (IRBs). The conversation covers five core ethical principles: voluntary participation, informed consent, confidentiality, disclosure, and accurate reporting. Through historical examples like the Nazi medical experiments and Tuskegee syphilis study, the hosts illustrate why ethics evolved to protect research participants. They discuss how key documents like the Nuremberg Code and Belmont Report established the ethical framework researchers follow today. The episode addresses special ethical considerations for vulnerable populations such as children, ethical challenges in online research, and the importance of cultural sensitivity. The hosts emphasize that ethical research requires ongoing reflection rather than simply following rules, and they provide practical guidance for navigating ethical dilemmas in research settings. This podcast was generated using NotebookLM.

23:51

S01:E02 May 20, 2025

Chapter 2: Research Foundations and Philosophy

This podcast examines the philosophical foundations of research methods. The hosts discuss ontology (beliefs about the nature of reality) and epistemology (how we gain knowledge), explaining how these fundamental positions shape research approaches. They explore key research paradigms including functionalism, interpretivism, radical structuralism, and radical humanism. The conversation clarifies the difference between paradigms and theories, with theories being specific explanations for phenomena that include constructs, propositions, logic, and assumptions. The hosts break down different types of variables (independent, dependent, mediating, moderating, control) and discuss criteria for evaluating theories, including logical consistency, explanatory power, falsifiability, and parsimony. The episode examines inductive approaches (building theory from observations) versus deductive approaches (testing existing theories), using real-world research examples to illustrate both methods. The hosts emphasize that these approaches often work together in an iterative cycle rather than being completely separate processes. This podcast was generated using NotebookLM.

24:41

S01:E01 May 18, 2025

Chapter 1: Introduction to Research Methods

This podcast explores the fundamental concepts of research methods in business. The hosts discuss how we acquire knowledge through different means including assumptions, direct experience, tradition, and observation. They explain the distinction between everyday ways of knowing and scientific approaches, covering the differences between natural and social sciences, as well as basic and applied research. The conversation includes key scientific concepts like laws, theories, and hypotheses, emphasizing that science is built on both logic and observation. The hosts explain experimental research designs and highlight the importance of falsifiability, replicability, precision, and parsimony in scientific research. The episode distinguishes between three main types of research: exploratory (initial investigation), descriptive (documenting what exists), and explanatory (understanding causes). It also addresses the unique challenges of business and marketing research, where human behavior adds complexity to establishing clear causal relationships. This podcast was generated using NotebookLM.