Lecture note on verification and falsification in quantitative data analysis: for MBA students

Lecture note on verification and falsification in quantitative data analysis: for MBA students

 

In the context of analyzing inferential statistics findings, e.g. from a questionnaire survey on my Hong Kong friends' opinion on CEO branding", how to practice verification and falsification on quantitative data analysis, in the context of doing an MBA dissertation projects. Please highlight 4 ideas on each of these two concepts (i.e. verification and falsification) in your discussion.

In an MBA dissertation using questionnaire data, verification means strengthening confidence that your statistical findings are credible, while falsification means actively trying to disconfirm your hypothesis rather than only looking for support. For your CEO-branding survey, the best practice is to treat every inferential result as a claim that must survive checks for consistency, sampling quality, and alternative explanations.studocu+1

Verification ideas

1.    Match the test to the hypothesis. If you predict that CEO branding is positively associated with purchase intention or trust, use the right inferential test for the variable types and research design, such as correlation, t-test, ANOVA, or regression. A result is more believable when the test logic fits the data structure and the study question.studocu

2.    Check whether the result is statistically and practically meaningful. Do not rely only on the p-value; report effect size and confidence interval as well, because inferential statistics are about estimating population patterns from a sample, not just labeling a result as significant. A small but significant effect may be weak in practical MBA terms, while a moderate effect may matter more for branding strategy.studocu

3.    Look for internal consistency across measures. If several questionnaire items measure the same concept, the pattern should broadly agree across related items, subscales, and descriptive statistics. Consistency across indicators makes your conclusion more trustworthy than a single isolated significant result.hkuspace.hku+1

4.    Use robustness checks. Re-run the analysis with sensible alternatives, such as checking assumptions, comparing parametric and non-parametric tests, or testing models with and without control variables. If the conclusion remains similar, your finding is better verified.studocu

Falsification ideas

1.    State a clear null hypothesis that can fail. For example, “CEO branding has no relationship with brand trust among Hong Kong respondents” is falsifiable because the data can contradict it. In dissertation work, hypotheses should be precise enough that evidence can show they are unsupported.arxiv+1

2.    Actively look for disconfirming patterns. Test whether the relationship disappears in subgroups, such as by age, work experience, or gender, or whether the effect reverses after adding controls. Falsification is not about forcing a rejection, but about asking whether the claim still holds under harder tests.studocu

3.    Check for alternative explanations and bias. A result that seems to support your hypothesis may actually reflect sampling bias, social desirability bias, poor wording, or non-response bias. Hong Kong survey quality guidance emphasizes careful questionnaire design, high response rates, and thorough checking of raw data to avoid misleading conclusions.studocu

4.    Try to reproduce the pattern with a different specification. If the effect only appears with one coding choice, one subset, or one analytic model, the claim is weak. A finding that survives re-coding, re-grouping, or alternative model assumptions is harder to falsify, and therefore stronger.studocu

Applying it to your survey

For an MBA dissertation, the key is to present verification and falsification as part of a disciplined analysis process, not as abstract philosophy. You can write that verification comes from consistency, significance, effect size, and robustness, while falsification comes from null hypotheses, subgroup testing, bias checks, and alternative model comparisons. That framing shows you are not merely “proving” your idea about CEO branding, but testing it rigorously in a way that supports sound managerial conclusions.hkuspace.hku+1

A simple way to phrase this in your dissertation is: “The analysis sought both to verify the hypothesized association between CEO branding and respondent perceptions and to falsify the claim by examining alternative explanations, robustness across subgroups, and sensitivity to model specification”.

** also study the video on Popper and the logic of falsification.

** A collection of lecture notes on the subject of research methods for MBA students, 2026 June

A collection of blog notes on using chatgpt for research purpose.

A collection of notes on MBA proposal brainstorming 2024-2026

A collection of notes on MBA proposal brainstorming 2024-2026

1. Discuss with Chatgpt to come up with a dissertation proposal based on a student's personal interest: a note for MBA students
2. A dialogue with Chatgpt to come up with a tailer-made dissertation proposal: a note for MBA students
3. Asking chatgpt to produce a dissertation proposal related to event management: for MBA students

4. An exploratory study on consumer culture and luxury marketing (Hong Kong and South Korea: a comparison): for MBA students

5. Asking chatgpt to produce a dissertation proposal on city brand experience study: for MBA students
6. Asking chatgpt to produce a proposal on impacts of AI on job content and professional development: for MBA students
7. An example to produce a preliminary dissertation proposal draft on the topic of "silver consumers": a note for MBA students; the exercise is done with the chatgpt tool via poe.com.
8. Asking poe.com to come up with a dissertation proposal about strategic decision making, managerial economics & pragmatism
9. Asking poe to produce a proposal on the etailing consumer behavior trends with scenario analysis: for MBA Students.
10. Asking poe.com to produce a proposal related to corporate productivity program and motivation theories: for MBA students
11. Asking perplexity to come up with a dissertation proposal based on 4 key words: (on elderly senior managers) for MBA students
12. An exploratory study on sustainable marketing strategies for the furniture sector: for MBA students
13. An exploratory study on strategy adaption to maintain competitive advantage for the Hong Kong dental clinic sector: for MBA students
14. An exploratory study on consumption downgrade: for MBA students

Lecture note on research types and their preferred research philosophies

Lecture note on research types and their preferred research philosophies 

Do different research types (i.e. descriptive, exploratory, causal and evaluation) tend to work better with a particular research philosophy (i.e. positivism, interpretivism, pragmatism and critical realism) in the context of doing a 4-month part-time MBA dissertation project?

Yes—there is a general fit, but it is not a strict one-to-one rule. For a 4-month part-time MBA dissertation, the clearest pattern is: descriptive research often fits positivism, exploratory research often fits interpretivism or pragmatism, causal research often fits positivism or critical realism, and evaluation research often fits pragmatism or critical realism.

Best-fit patterns

·        Descriptive research usually sits well with positivism because it is about measuring and summarizing “what is happening” through observable, structured data such as surveys or secondary statistics.

·        Exploratory research often fits interpretivism because it aims to discover meanings, generate ideas, and understand context through qualitative inquiry.

·        Causal research tends to fit positivism when you want to test variable relationships statistically, but critical realism can be a better philosophical home if you want to explain underlying mechanisms rather than just correlations.

·        Evaluation research often fits pragmatism because MBA projects usually need actionable findings, but critical realism is also strong when the evaluation needs to explain why an intervention worked or did not work.

Practical MBA fit

For a 4-month part-time MBA dissertation, pragmatism is often the safest default because it lets you choose methods based on what answers the business question most efficiently, including mixed methods if needed. That said, if your project is tightly quantitative and mainly descriptive or causal, positivism is usually easier to justify and faster to execute. If your project is about a complex organisational or policy issue and you need both measurable outcomes and deeper explanation, critical realism can be very persuasive.

Simple matching guide

Research type	Often fits best		Why
Research type		Often fits best		Why
Descriptive		Positivism		Measures patterns, frequency, and status using structured data
Exploratory		Interpretivism or pragmatism		Seeks insight, meaning, and flexibility when the problem is not well defined
Causal		Positivism or critical realism		Tests relationships; critical realism adds explanation of mechanisms
Evaluation		Pragmatism or critical realism		Focuses on usefulness, outcomes, and “what worked, why, and under what conditions”

Dissertation strategy

If your time is limited to 4 months, the safest design is usually to keep the philosophy aligned with the simplest defensible method set. In practice, that means a survey-based descriptive or causal project can be framed in positivist terms, while an interview-plus-documents or mixed-method evaluation project is often better framed pragmatically. If your supervisor expects deeper explanation of organisational outcomes, critical realism can strengthen the logic without forcing you into a purely quantitative or purely qualitative box.

** A collection of lecture notes on the subject of research methods for MBA students, 2026 June

A collection of blog notes on using chatgpt for research purpose.

Lecture note on research methods design criteria for mixed methods research design: for MBA students

Lecture note on research methods design criteria for mixed methods research design: for MBA students

 

Highlight 3 main research methods design criteria and offer 3 practice advices on how to improve the mixed methods research design, based on pragmatism, in the context of doing a part-time fourth-month MBA dissertation project.

For a part-time MBA dissertation using mixed methods research grounded in pragmatism, the three main design criteria and three practical improvement advice are:

Three Main Research Design Criteria (Pragmatism-Based)

According to pragmatist mixed methods literature, design decisions should be:

Criterion	What It Means for Your MBA Dissertation
Practical	The design must work within your part-time constraints (4 months elapsed, limited time access to participants, word limits)
Contextually responsive	The design must fit your specific business/MBA context—addressing real organizational problems rather than abstract theory
Consequential	The design must produce findings that matter—solutions or insights with actual application value for business practice

Pragmatism places the research question at the center and links all methodological decisions to answering it, rather than prioritizing methods themselves.

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Three Practice Advices to Improve Your Mixed Methods Design

1. Treat integration as a third strand—not just "two halves"

Mixed methods has three components: qualitative strand + quantitative strand + integration. Don't just collect both types of data; explicitly plan how you'll pull them together to generate insight "greater than the sum of the parts".

·        Action: In your methods section, write a dedicated subsection on integration plans—how you'll triangulate, compare, or weave qualitative and quantitative findings together.

2. Start writing the methods section immediately

At month 4 of a part-time dissertation, you're at a critical juncture. Writing what you're doing and how reveals holes in your research plan before you waste time.

·        Action: Draft your methods section now, including data collection procedures, analysis plans, and integration strategy. This will help you identify access issues, timeline problems, or overly broad questions.

3. Align research questions tightly with feasible methods

For part-time students, a common pitfall is asking questions too broad for the timeline. Each question must be realistically answerable through your chosen interviews/surveys/case evidence.

·        Action: Apply the "few sentences test": if you can't explain in 2–3 sentences how your data will answer each question, the design is too wide. Narrow your topic, reduce sample size, or focus on one core business problem.

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Key pragmatism reminder: Ask "what works" for your research problem, not what's methodologically pure. Use methods instrumentally based on applicability to your MBA context.

Please clarify your ideas a bit with regard to the MBA dissertation research theme of "to evaluate the influence of corporate talent management policy on the middle-managers' innovation behavior in ABC Hotel Ltd of Hong Kong via the lens of pragmatism, using semi-structured interview, employee questionnaire survey and internal document study".

 

Let me clarify how those pragmatist design criteria and improvement advice apply directly to your MBA dissertation theme:

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Your Research Theme Breakdown

Topic: Evaluate how corporate talent management policy influences middle managers' innovation behavior at ABC Hotel Ltd, Hong Kong
Philosophy: Pragmatism
Methods: Semi-structured interviews + employee questionnaire survey + internal document study (mixed methods: qualitative + quantitative + document analysis)

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How the Three Design Criteria Apply to Your Study

1. Practical → Works within your part-time constraints

Constraint	How Your Design Must Adapt
4 months elapsed (June 2026)	You likely have ~8–12 months remaining. Interviews + survey + document study is ambitious but feasible if you limit sample sizes
Part-time MBA (working professional)	Use ABC Hotel's existing middle managers as accessible participants—no need for external recruitment
Hong Kong context	Single organization (ABC Hotel Ltd) = manageable scope; avoid multi-company comparison

Pragmatist check: Does combining three methods genuinely help answer your question better than just one? Yes—interviews reveal why policies affect behavior, surveys show how much and how widespread, documents verify what policies actually exist.

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2. Contextually responsive → Fits ABC Hotel's business reality

Your design must reflect:

·        Hotel industry specifics: Middle managers in hotels face unique pressures (guest service, shift work, high turnover) that shape innovation behavior differently than manufacturing/tech sectors

·        Hong Kong labor market: High competition for talent, multicultural workforce, regulatory environment around talent management

·        ABC Hotel's actual policy: Don't study "talent management" abstractly—focus on their specific policy (e.g., training programs, performance appraisal, career development pathways)

Pragmatist check: Are your interview questions and survey items grounded in hotel middle managers' daily work? Example:

·        Interview: "How does ABC Hotel's training policy affect your ability to try new service approaches with guests?"

·        Survey: "On a 1–5 scale, how much does the career development policy encourage you to propose innovation ideas?"

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3. Consequential → Produces findings with real business value

Your dissertation should answer:

·        For ABC Hotel: "Should we revise our talent management policy to boost middle managers' innovation?"

·        For Hong Kong hotel industry: "What talent management practices work for encouraging innovation in service businesses?"

·        For MBA learning: "How does stakeholder theory/pragmatism explain the policy-behavior link?"

Pragmatist check: Will your findings lead to actionable recommendations? If yes, the design is consequential. Avoid purely theoretical conclusions.

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How the Three Improvement Advices Apply to Your Design

Advice 1: Treat integration as a third strand

Your three methods must be intentionally woven together, not just reported separately:

Method	What It Reveals	How to Integrate
Semi-structured interviews (qualitative)	Deep understanding of why and how policy influences behavior; personal stories, barriers, motivations	Use interview themes to explain survey patterns (e.g., "Survey showed 40% feel policy discourages innovation; interviews revealed this is because...")
Employee questionnaire survey (quantitative)	Statistical patterns: strength of relationship, prevalence across departments, demographic differences	Survey results guide which interview participants to select (e.g., target low-innovation scorers for deeper interviews)
Internal document study	Objective verification of policy content, implementation guidelines, HR records	Documents confirm what policies actually exist vs. what employees report in survey/interviews

Integration example:

"Survey data showed middle managers in the Front Office department scored innovation behavior 1.5 points lower than Rooms Division (p<0.05). Interview analysis revealed Front Office managers face stricter guest-service protocols limiting experimentation. Document review confirmed Front Office has more rigid talent management procedures. Together, these explain why the policy's influence varies by department."

This is integration—not just "qualitative said X, quantitative said Y" but "qualitative + quantitative + documents = deeper insight".

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Advice 2: Start writing the methods section immediately

At month 4, draft your methods section now to expose problems:

What to write now:

1.    Sampling strategy: How many interviewees? How many survey respondents? How do you select ABC Hotel middle managers?

2.    Data collection timeline: When will you conduct interviews? When will survey launch/close? When will you access documents?

3.    Analysis plan: How will you analyze interview transcripts (e.g., thematic analysis)? How will you analyze survey data (e.g., SPSS regression)? How will you analyze documents (e.g., policy content coding)?

4.    Integration plan: Explicitly describe when and how you'll combine methods (e.g., "After survey analysis, I will select interview participants based on survey scores")

Common pitfalls you'll catch:

·        Can you realistically get 50+ survey respondents from ABC Hotel middle managers in 2 months?

·        Do you have HR approval to access internal documents?

·        Are your interview questions aligned with survey items for integration?

Writing reveals these gaps before you waste time.

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Advice 3: Align research questions tightly with feasible methods

Your current theme is one broad question. Break it into 2–3 focused sub-questions that your methods can actually answer:

Suggested research question structure:

Question	Method That Answers It	Feasibility Check
RQ1: What is the content and implementation of ABC Hotel's corporate talent management policy?	Internal document study	✅ Easy (HR documents)
RQ2: How strongly does the talent management policy correlate with middle managers' innovation behavior?	Employee questionnaire survey (regression analysis)	✅ Needs 30–50 respondents
RQ3: How do middle managers perceive and experience the policy's influence on their innovation behavior?	Semi-structured interviews (thematic analysis)	✅ Needs 8–12 participants
RQ4: How do survey patterns, interview insights, and document evidence combine to explain the policy-behavior relationship?	Integration of all three methods	⚠️ Requires careful planning

Why this works:

·        Each RQ is answerable by one or more methods

·        No RQ is too broad ("evaluate the influence" → broken into correlation + perception + mechanism)

·        Integration (RQ4) ties everything together pragmatically

Pragmatist reminder: If you can't explain in 2–3 sentences how your data answers RQ2, the question is too wide. Narrow it: "What is the correlation coefficient between policy satisfaction score and innovation behavior score?".

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Pragmatism in Your Specific Context

Why pragmatism fits your study:

Pragmatist Principle	Your Study Application
Research question drives methods	You chose interviews + survey + documents because together they best answer "how policy influences behavior"
"What works" over methodological purity	You're not doing pure qualitative OR pure quantitative—you're using what's practical for a hotel business problem
Real-world problem solving	Your findings will help ABC Hotel improve talent policy to boost innovation
Multiple truths acknowledged	Documents show policy what, survey shows policy extent, interviews show policy experience—all valid perspectives

Avoid positivism trap: Don't assume survey correlation = "objective truth." Pragmatism says survey + interviews + documents = better understanding than any single method.

Avoid interpretivism trap: Don't assume only interviews reveal "real meaning." Pragmatism says survey statistics also matter for business decisions.

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Quick Feasibility Checklist for Your Part-Time MBA (Month 4)

Task	Timeline	Risk
Get HR approval for documents & survey access	Week 1–2	⚠️ High—if delayed, entire project stalls
Draft interview questions + survey items	Week 2–3	✅ Medium—can revise
Conduct 8–12 semi-structured interviews	Week 4–8	⚠️ Medium—scheduling with working managers
Launch survey to 30–50 middle managers	Week 5–10	⚠️ Medium—response rate uncertainty
Analyze interview transcripts (thematic)	Week 9–12	✅ Low—doable alone
Analyalyze survey data (SPSS/Excel)	Week 11–14	✅ Low—standard stats
Analyze documents (content coding)	Week 10–12	✅ Low
Integrate findings (write RQ4)	Week 13–16	⚠️ High—requires careful thinking
Write full dissertation	Week 17–24	⚠️ Medium—time pressure

Key advice: Start methods section draft this week. If HR approval takes 3 months instead of 2, you need to adjust timeline immediately.

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Your design is pragmatically sound if you:

1.    Keep scope single-organization (ABC Hotel)

2.    Limit sample sizes realistically (12 interviews, 40 survey respondents)

3.    Plan integration explicitly (not just "methods A + B")

4.    Write methods section now to expose gaps

5.    Focus RQs on actionable business insights, not abstract theory

This approach respects your part-time constraints while producing consequential findings for Hong Kong's hotel industry.

 

** A collection of lecture notes on the subject of research methods for MBA students, 2026 June

A collection of blog notes on using chatgpt for research purpose.