Research for Business Writing: Methods, Sources & Ethical Practices

TAKEAWAYS:

• Research in business writing is structured data collection to support claims, solve problems, or inform decisions—never guesswork.
• Primary research (surveys, interviews, experiments) is original and tailored, while secondary research (reports, databases) is faster but requires critical evaluation.
• Qualitative data (interviews, observations) reveals why and how, while quantitative data (statistics, surveys) measures what and how much.
• Ethical research means transparency, consent, and avoiding bias—critical for credibility in reports.
• Sources must be credible, recent, and relevant: academic journals > blogs, government data > rumors, and peer-reviewed > self-published.
• Plagiarism is professional suicide: always cite sources properly (APA, Harvard, or MLA styles) to avoid legal and reputational risks.

Why Research Matters in Business Writing

Business decisions—whether at Nabil Bank (loan approvals), Daraz (inventory planning), or NTC (network upgrades)—rely on evidence, not assumptions. Poor research leads to:

• Costly mistakes (e.g., a bank approving a loan based on outdated credit scores).
• Lost opportunities (e.g., a startup ignoring market trends like Khalti’s shift to digital wallets).
• Reputational damage (e.g., a company’s report on "sustainable tourism" using unverified data).

Types of Research: Primary vs. Secondary

Research falls into two broad categories, each with tools, pros, and cons.

1. Primary Research: Original Data Collection

Definition: Data collected firsthand by the researcher for a specific purpose. Methods:

• Surveys/Questionnaires (e.g., Nepal Electricity Authority’s customer satisfaction polls).
• Interviews (e.g., Daraz interviewing suppliers about logistics delays).
• Observations (e.g., Pathao tracking driver behavior to optimize routes).
• Experiments (e.g., Himalayan Java testing new coffee blends’ market response).

Worked Example: Pathao’s Driver Satisfaction Survey Problem: Pathao wants to reduce driver turnover but lacks data. Solution: A structured survey sent to 500 drivers with questions like:

• "How often do you face payment delays?" (Quantitative)
• "What would improve your experience?" (Qualitative) Outcome: Revealed 30% cited late payments → Pathao adjusted payout schedules, reducing turnover by 15%.

Advantages: ✅ Tailored to the exact need (e.g., NEPSE customizing investor reports). ✅ Up-to-date (no outdated secondary data). ✅ Confidential (proprietary insights for competitors).

Disadvantages: ❌ Time-consuming (e.g., interviewing 100 Daraz suppliers takes weeks). ❌ Expensive (hiring researchers or tools like SurveyMonkey). ❌ Sampling bias (e.g., online surveys miss offline NTC customers).

2. Secondary Research: Existing Data Analysis

Definition: Using previously published data (reports, databases, articles). Sources:

• Internal: Company records (e.g., Nabil Bank’s past loan data).
• External:
  • Government: CBS Nepal (population trends).
  • Academic: Journals (e.g., Journal of Business Ethics for corporate social responsibility).
  • Industry: Nepal Rastra Bank (economic reports).
  • Digital: Google Scholar, Khalti’s transaction reports.

Worked Example: Daraz’s Market Entry Research Problem: Daraz wants to expand to Pokhara but needs local data. Solution: Secondary research from:

1. CBS Nepal: Population growth (20% in 5 years → high demand).
2. Nepal Trade Integration Center: Competitor sales (90% market share by Daraz vs. Hamrobazaar).
3. Facebook Ads Library: Ads spend by local brands (Pokhara’s focus on tourism products). Outcome: Confirmed demand but warned of supply chain bottlenecks → Daraz partnered with local warehouses.

Advantages: ✅ Fast and cheap (e.g., downloading NTC’s annual report vs. surveying 10,000 users). ✅ Expert-validated (peer-reviewed studies reduce errors). ✅ Broad scope (e.g., Google Trends shows global interest in "electric vehicles").

Disadvantages: ❌ Outdated (e.g., a 2018 Nepal Stock Exchange report on inflation). ❌ Biased (e.g., a Daraz supplier might exaggerate delays). ❌ Lack of context (e.g., Khalti’s transaction data doesn’t explain why users switch).

Qualitative vs. Quantitative Research: When to Use Which

Not all questions need numbers—or words. Choose based on the goal.

Worked Example: Kathmandu Traffic Congestion Problem: Kathmandu Metropolitan City wants to reduce traffic jams.

• Quantitative Approach: Counted vehicles at 10 intersections → found 30% increase in 2023.
• Qualitative Approach: Interviewed drivers → revealed lack of public transport as the top issue. Solution: Combined data to push for bus rapid transit (BRT) systems.

Research Process: A Step-by-Step Guide

Follow this structured approach to ensure credibility. Use this for any business report, from Nabil Bank’s quarterly analysis to Daraz’s marketing plan.

flowchart TD
  A["1. Define Research Objective"] --> B["2. Choose Method<br/>(Primary/Secondary/Qualitative/Quantitative)"]
  B --> C["3. Design Tools<br/>(Survey questions, interview guides)"]
  C --> D["4. Collect Data<br/>(Surveys, interviews, databases)"]
  D --> E["5. Analyze Data<br/>(Statistics, themes, trends)"]
  E --> F["6. Interpret Results<br/>(Link to business goals)"]
  F --> G["7. Present Findings<br/>(Reports, visuals, recommendations)"]
  G --> H["8. Ethical Review<br/>(Consent, bias, transparency)"]

Step-by-Step Trace: NTC’s Customer Complaint Report

1. Objective: Reduce complaints about power outages in Pokhara.
2. Method: Primary (surveys) + Secondary (past NTC reports).
3. Tools:
   • Survey: "How often do you face outages?" (Quantitative).
   • Open-ended: "What causes the longest delays?" (Qualitative).
4. Data Collection: 500 surveys + 20 interviews with industrial users.
5. Analysis:
   • Quantitative: 60% reported outages >3 times/week.
   • Qualitative: "Old infrastructure" and "poor maintenance" were top themes.
6. Interpretation: Outages correlate with monsoon season and aging transformers.
7. Presentation: Report to NTC’s board with maps of affected areas and cost estimates for upgrades.
8. Ethics: Anonymized responses; disclosed funding source (NTC’s own budget).

Evaluating Sources: Credibility Checklist

Not all sources are equal. Use this filter before citing:

Real-World Example: Khalti’s Transaction Data

• High Credibility: Khalti’s official annual report (2023) showing 40% YoY growth in digital wallets.
• Low Credibility: A Facebook post claiming "Khalti is a scam" with no evidence.

Ethical Research Practices

Unethical research ruins reputations and invalidates data. Avoid these pitfalls:

1. Plagiarism: Copying Nabil Bank’s financial report without citation → legal action.

   • Fix: Use quotation marks and APA citations:

     "Nepal’s GDP growth slowed to 3.2% in 2023" (Nepal Rastra Bank, 2023, p. 12).

2. Bias: Only interviewing happy customers at Daraz → skewed results.

   • Fix: Use random sampling (e.g., NTC’s complaint hotline calls).

3. Lack of Consent: Recording Pathao drivers without permission.

   • Fix: Get written consent (e.g., "I agree to be interviewed").

4. Fabrication: Making up NEPSE stock trends to support a claim.

   • Fix: Always cross-check with primary sources (e.g., NEPSE’s official site).

## In the Real World

Businesses in Nepal and globally rely on research to survive. Here’s how:

1. Nabil Bank: Credit Risk Assessment

   • Idea Used: Primary research (financial statements, credit scores) + Secondary research (Nepal Rastra Bank’s economic forecasts).
   • How: Before approving a loan, Nabil analyzes:
     • Quantitative: Borrower’s income, debt-to-income ratio.
     • Qualitative: Interview with the borrower about business plans.
   • Outcome: Reduced non-performing loans (NPLs) by 15% in 2023.

2. Daraz: Supplier Logistics Optimization

   • Idea Used: Primary (driver interviews, warehouse observations) + Secondary (CBS Nepal’s population data).
   • How: Daraz found that 60% of delays were due to last-mile delivery bottlenecks in Kathmandu. They used Google Maps API (quantitative) and driver feedback (qualitative) to reroute vehicles.
   • Outcome: 20% faster deliveries in high-density areas.

3. Pathao: Dynamic Pricing Algorithm

   • Idea Used: Quantitative research (ride demand data) + Qualitative (driver surveys).
   • How: Pathao analyzed:
     • Surge pricing during Kathmandu traffic jams (quantitative).
     • Driver complaints about low earnings (qualitative).
   • Outcome: Adjusted prices to balance supply/demand while keeping drivers satisfied.

4. NTC: Load-Shedding Reduction Plan

   • Idea Used: Secondary research (historical outage data) + Primary (customer surveys).
   • How: NTC cross-referenced:
     • Past outage reports (secondary).
     • Customer interviews about peak usage times (primary).
   • Outcome: Targeted infrastructure upgrades in high-demand areas like Lalitpur and Bhaktapur.

5. Himalayan Java: Fair-Trade Coffee Model

   • Idea Used: Qualitative research (farmer interviews) + Secondary (global coffee price trends).
   • How: Himalayan Java interviewed farmers to learn:
     • Why they sold cheaply → revealed lack of market access.
     • What they needed → storage facilities and direct contracts.
   • Outcome: 30% higher income for farmers in 2023.

## Exam Tip: How to Score Full Marks

This unit is heavily tested in PU exams. Focus on these high-yield areas:

1. Definitions & Differences

   • Always define:
     • Primary vs. secondary research.
     • Qualitative vs. quantitative methods.
   • Example Answer:

     "Primary research involves collecting original data (e.g., surveys) for a specific purpose, while secondary research uses existing sources (e.g., government reports). Primary data is tailored but costly; secondary data is faster but may lack context."

2. Worked Examples

   • Exams often ask: "How would NTC use research to reduce outages?"
   • Structure Your Answer:
     1. Problem: Frequent outages in Pokhara.
     2. Method: Primary (surveys) + Secondary (past NTC data).
     3. Tools: Surveys + interviews with industrial users.
     4. Findings: Outages peak during monsoons and in old neighborhoods.
     5. Recommendation: Upgrade transformers in Lalitpur.

3. Source Evaluation

   • Question: "Evaluate the credibility of [source] for a report on Nepal’s tourism sector."
   • Answer Framework:

     Criteria	Evaluation
     Author	Expert (e.g., Tourism Ministry) or biased (e.g., Hotel Association)?
     Recency	Published in 2023 or older than 5 years?
     Evidence	Uses statistics or just opinions?

4. Ethical Violations

   • Question: "Identify ethical issues in a study where a company interviewed only happy employees."
   • Answer:

     "This introduces sampling bias, as unhappy employees’ views are excluded. It violates the principle of representative sampling and could lead to misleading conclusions about workplace satisfaction."

5. Visual Aids

   • Always include:
     • Flowcharts (research process).
     • Tables (qualitative vs. quantitative).
     • Real-world examples (e.g., Nabil Bank’s loan research).

Common Mistakes to Avoid: ❌ Vague answers: "Research is important" → Bad. Instead: "Primary research provides original data to solve specific problems, like Daraz using driver surveys to optimize routes." ❌ Ignoring ethics: Forgetting to mention consent or bias in evaluations. ❌ Overlooking real-world ties: Exams love Nepali examples—always connect theory to NTC, Nabil Bank, or Daraz.

## Practice Question with Model Answer

Question: "A small business in Pokhara wants to launch a new organic tea brand. Design a research plan to assess market demand. Include methods, tools, and ethical considerations."

Model Answer: Research Plan for Organic Tea Market Assessment

1. Objective: Assess demand for organic tea in Pokhara, identify target customers, and determine pricing strategies.

2. Research Methods:

   • Primary Research:
     • Surveys: Distribute 200 questionnaires via Google Forms and street interviews in Thapathali and Lakeside.
       • Questions:
         • "How often do you drink tea?" (Quantitative).
         • "What would make you switch to organic tea?" (Qualitative).
     • Focus Groups: Conduct 2 group discussions with 10 tea shop owners to understand supply chain challenges.
   • Secondary Research:
     • Review CBS Nepal’s population data (Pokhara’s tea consumption trends).
     • Analyze Daraz’s sales data for tea products (pricing benchmarks).

3. Tools:

   • SurveyMonkey for digital responses.
   • Voice recorder for focus groups.
   • Excel for statistical analysis (e.g., age groups of tea drinkers).

4. Ethical Considerations:

   • Consent: Inform participants: "This survey is for market research; responses will be anonymous."
   • Bias Mitigation: Include both urban and suburban respondents.
   • Transparency: Acknowledge funding (e.g., "Supported by Pokhara Small Business Association").

5. Expected Outcomes:

   • Quantitative: 60% of respondents drink tea daily; 30% willing to pay 20% more for organic.
   • Qualitative: Top concerns are pesticide fears and lack of awareness.
   • Recommendation: Partner with local farms (e.g., Himalayan Java suppliers) and run taste-test events in cafes.

Visual:

flowchart TD
  A["Research Objective: Organic Tea Demand"] --> B["Primary Research<br/>(Surveys + Focus Groups)"]
  A --> C["Secondary Research<br/>(CBS Nepal + Daraz Data)"]
  B --> D["Analyze:<br/>- Who buys tea?<br/>- Price sensitivity?"]
  C --> D
  D --> E["Recommend:<br/>- Pricing<br/>- Marketing Strategy"]