Dean's Office Official Model Question Paper

Basic vs. Applied Research

• Basic (Fundamental) Research: Aims to expand theoretical knowledge and formulate universal academic principles without immediate practical application.
• Applied Research: Designed to solve specific, practical operational problems faced by managers in real-world business organizations.

Variables in Research

• Independent Variable ($X$): The variable that is manipulated or presumed to cause changes in the outcome variable (e.g., Hotel Employee Training Hours).
• Dependent Variable ($Y$): The outcome variable measured to see the effect of the independent variable (e.g., Guest Satisfaction Rating).

Likert Scale

A psychometric rating scale used in questionnaire surveys where respondents specify their level of agreement with a statement across an ordered continuum.

• Example: 1 = Strongly Disagree, 2 = Disagree, 3 = Neutral, 4 = Agree, 5 = Strongly Agree.

Probability vs. Non-Probability Sampling

• Probability Sampling: Every element in the target population has a known, non-zero chance of being selected (e.g., Simple Random, Stratified).
• Non-Probability Sampling: Elements are selected based on subjective managerial convenience or judgment without known probability (e.g., Convenience, Purposive).

Type I vs. Type II Error

• Type I Error ($\alpha$): Rejecting the true null hypothesis ($H_0$) when it should have been accepted (‘false positive’).
• Type II Error ($\beta$): Failing to reject a false null hypothesis when it should have been rejected (‘false negative’).

The Scientific Business Research Process

1. Identify the Broad Management Dilemma: Observing operational inefficiencies (e.g., declining repeat guest rates).
2. Preliminary Literature Review: Reviewing relevant academic journals and textbooks to contextualize the problem.
3. Problem Formulation & Research Questions: Defining precise, researchable questions and operational definitions.
4. Theoretical Framework & Hypothesis Development: Mapping relationships between independent, mediating, and dependent variables.
5. Research Design: Selecting qualitative, quantitative, or mixed-methods research architecture.
6. Measurement & Instrument Design: Developing structured survey questionnaires or interview protocols.
7. Sampling Design: Defining target population, sample frame, sampling method, and calculating sample size.
8. Data Collection: Administering field surveys, digital questionnaires, or observational audits.
9. Data Processing & Statistical Analysis: Editing, coding, testing hypotheses via descriptive and inferential statistics (SPSS/R).
10. Report Writing & Executive Presentation: Synthesizing findings, acknowledging limitations, and presenting actionable managerial recommendations.

Questionnaire Design Principles in Hospitality

1. Logical Question Flow (Funnel Approach):
   • Opening: Simple, welcoming screening questions establishing rapport.
   • Body: Specific operational rating questions grouped by department (Front Office, Housekeeping, Dining).
   • Closing: Sensitive demographic questions (age, income bracket) placed at the end.
2. Avoid Bias and Flaws:
   • Avoid Leading Questions: Never write “Don’t you agree our restaurant food was delicious?” (Instead: “How would you rate the taste of the food?”).
   • Avoid Double-Barreled Questions: Do not combine two issues in one item: “How satisfied were you with the room cleanliness and Wi-Fi speed?” (Split into two separate items).
   • Avoid Jargon: Use plain language easily understood by non-native speakers.
3. Pilot Testing (Pre-Testing):
   • Administer the draft survey to 20–30 representative guests to check for ambiguous phrasing, cognitive fatigue, and average completion time before full deployment.

Comparative Analysis of Sampling Techniques

1. Probability Sampling Methods:

• Simple Random Sampling: Each population unit has an equal chance; selected via random number generators.
• Stratified Random Sampling: Population divided into mutually exclusive strata (e.g., Room types: Standard, Deluxe, Suite); random samples drawn from each stratum proportionally.
• Systematic Sampling: Selecting every $k$-th item from a list ($k = N/n$) after a random start.
• Cluster Sampling: Dividing geographic population into natural clusters (e.g., tourist districts) and surveying all units within randomly selected clusters.

2. Non-Probability Sampling Methods:

• Convenience Sampling: Surveying accessible individuals (e.g., intercepting guests sitting in the hotel lobby).
• Purposive (Judgmental) Sampling: Selecting specific experts possessing required knowledge (e.g., interviewing Executive Chefs on menu engineering).
• Quota Sampling: Fulfilling specified demographic quotas without random selection.
• Snowball Sampling: Initial participants refer additional contacts with rare attributes (e.g., extreme mountaineering trekkers).

Structure of BHM Project Report / Dissertation

1. Preliminary Pages:
   • Title Page, Recommendation from Supervisor, Viva Voce Evaluation Committee Certificate, Declaration of Originality, Acknowledgments, Table of Contents, List of Tables, List of Figures, Executive Summary / Abstract.
2. Chapter I: Introduction:
   • Background of the Study, Statement of the Problem, Research Objectives, Research Hypotheses, Significance of the Study, Limitations of the Study.
3. Chapter II: Literature Review:
   • Conceptual/Theoretical Review, Empirical Review of Past Studies, Research Gap, Conceptual Framework.
4. Chapter III: Research Methodology:
   • Research Design, Population and Sample, Sources of Data, Instrumentation and Measurement, Reliability and Validity, Data Analysis Tools.
5. Chapter IV: Results and Discussion:
   • Demographic Profile of Respondents, Descriptive Analysis of Variables, Inferential Statistical Hypothesis Testing, Discussion of Findings against prior literature.
6. Chapter V: Summary, Conclusion, and Recommendations:
   • Summary of Findings, Theoretical and Managerial Conclusions, Actionable Recommendations for Hoteliers.
7. Supplementary Section: References (APA 7th edition), Survey Questionnaire, Raw Data Tables.

Empirical Research Proposal Dossier: Green Hospitality & Guest Loyalty

a. Problem Statement, Research Questions & Hypotheses

• Problem Statement: While luxury hotels in Nepal are investing capital in eco-friendly retrofits, empirical evidence regarding whether these green initiatives enhance brand equity and drive repeat bookings among international and domestic tourists remains fragmented.
• Research Questions:
  1. What is the extent of green practice adoption across Kathmandu 5-star hotels?
  2. How do green hotel practices influence perceived brand image?
  3. Does perceived brand image mediate the relationship between green practices and guest brand loyalty?
• Research Hypotheses:
  • $H_1$: Green hotel practices have a statistically significant positive effect on brand image.
  • $H_2$: Perceived brand image has a statistically significant positive effect on guest loyalty.
  • $H_3$: Green hotel practices have a statistically significant positive direct and indirect effect on guest loyalty.

b. Conceptual Framework

$$\text{[Green Practices: Energy, Waste, Sourcing (IV)]} \longrightarrow \text{[Perceived Brand Image (Mediator)]} \longrightarrow \text{[Guest Brand Loyalty \& Revisit Intention (DV)]}$$

c. Research Methodology

• Research Design: Quantitative, descriptive, and cross-sectional explanatory survey design.
• Population & Sample Size: Inbound international and domestic guests staying at verified 5-star hotels in Kathmandu. Using Cochran’s sample formula for large populations ($e = 0.05, Z = 1.96$), minimum sample size is calculated as $n = 384$ respondents.
• Sampling Technique: Stratified convenience sampling across six 5-star properties in Kathmandu.
• Instrumentation: 5-point Likert Scale questionnaire (1 = Strongly Disagree to 5 = Strongly Agree) adapted from validated scales in prior literature.

d. Statistical Analysis Plan

1. Data Screening & Reliability: Test internal consistency of scale items using Cronbach’s Alpha (benchmark $\alpha \ge 0.70$).
2. Descriptive Statistics: Calculate mean and standard deviation for green practice dimensions.
3. Multiple Linear Regression Modeling:
   $$\text{Guest Loyalty} = \beta_0 + \beta_1(\text{Energy Saving}) + \beta_2(\text{Waste Reduction}) + \beta_3(\text{Local Sourcing}) + \beta_4(\text{Brand Image}) + \epsilon$$
   Evaluate model fit using $R^2$, $F$-statistic, and assess individual regression coefficients using $t$-tests at $p < 0.05$.