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Destination Image and Revisit Intention at Hampi: An Importance–Performance Analysis of Domestic and Foreign Tourists

  • 12 slides
  • 14 viva questions
  • 5 modules
  • No code needed

@hampi-destination-image-revisit-intention-ipa-surveyUpdated Oct 2026

A 300-visitor survey that maps what tourists value at a World Heritage Site against how well Hampi delivers it

MHM, Travel & Tourism · Sem 4 · Intermediate · 14 weeks · Solo

More info
Level
Intermediate · 14 weeks · Solo
Relevant for
All India
Common at
NCHMCT (National Council for Hotel Management & Catering Technology)
Syllabus
NCHMCT NCHMCT-JNU · BHA401 / BHA402 Industrial Training Feedback Appraisal + Project Report · Semester 4
Tech stack
  • Structured tourist questionnaire (bilingual, 5-point)
  • Importance–Performance Analysis (Martilla & James)
  • SPSS (t-test, paired t-test, regression, reliability)
  • MS Excel (IPA grid charts)
  • Secondary data: Ministry of Tourism and Karnataka Tourism statistics
  • Google Forms / printed questionnaires
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  1. Pinned

    1 min

    Overview

    Hampi, the ruined capital of the Vijayanagara empire and a UNESCO World Heritage Site in Karnataka's Vijayanagara district, draws backpackers, pilgrims, school groups, history enthusiasts and international travellers. Visitors praise its boulder landscapes and temples, yet many also complain about local transport, signage, toilets, food choices and information at monuments. The question this project answers is simple and practical: which attributes of Hampi matter most to tourists, and how well does the destination perform on exactly those attributes?

    The study uses Importance–Performance Analysis (IPA), introduced by Martilla and James (1977). About 300 tourists — domestic and foreign — rate around 22 destination attributes twice: once for how important each attribute is to them and once for how Hampi performed during their visit. Attributes cover heritage and attractions, natural scenery, accessibility and local transport, accommodation, food, cleanliness and sanitation, safety, information and interpretation, local community and value for money. Plotting mean importance against mean performance produces the four IPA quadrants: Concentrate Here, Keep Up the Good Work, Low Priority and Possible Overkill.

    The analysis is done in SPSS and Excel: reliability of the scale, paired t-tests for importance–performance gaps, independent t-tests comparing domestic and foreign visitors, and a regression of revisit and recommend intention on destination-image dimensions. Published Ministry of Tourism and Karnataka Tourism statistics provide context on visitor trends. The recommendations are written for the destination's stakeholders — hotels, homestays, tour operators and the local tourism authorities.

    Syllabus alignment

    NCHMCT · NCHMCT-JNU

    BHA401 / BHA402 · Industrial Training Feedback Appraisal + Project Report · Semester 4 · 20 credits · 200 + 100

    Subjects this project applies
    • Tourism Marketing — destination image and positioning
    • Travel and Tourism Management — heritage tourism and visitor management
    • Research Methodology — sampling, questionnaire design and SPSS
    • Hospitality and Tourism Economics — tourism statistics and demand
    • Guest service management — service quality in tourism
    How it is evaluated

    See your department's project guidelines.

    1 min read · 14 viva questions

  2. 2 min

    Synopsis

    Abstract

    Destination image — the beliefs and impressions tourists hold about a place — influences whether they return and whether they recommend the place to others. This study assesses the destination image of Hampi using Importance–Performance Analysis. A structured questionnaire rating 22 attributes on importance and performance was administered to about 300 domestic and foreign tourists at major sites. SPSS was used to test reliability, importance–performance gaps and differences between domestic and foreign visitors, and to model revisit intention. The IPA grid identifies attributes requiring urgent attention and those where effort may be excessive, offering evidence-based priorities for destination management.

    Introduction

    Heritage destinations face a double task: protecting monuments and serving visitors. Hampi's monuments are managed by the Archaeological Survey of India, while roads, transport, sanitation, accommodation and guiding depend on local bodies, state tourism agencies and private operators. Tourists experience all of these as a single "Hampi", so a weak link anywhere affects the overall image.

    Review and gap

    Destination-image research distinguishes cognitive image (beliefs about attributes) from affective image (feelings), and links image to satisfaction and loyalty. IPA has been widely used in tourism because its grid is easy for managers to read. Indian heritage-site studies often report satisfaction levels alone, without separating what visitors value from how the site performs, and few compare domestic and foreign visitors on the same attributes. This study fills that gap for Hampi.

    Hypotheses

    • H1: There is a significant gap between importance and performance for infrastructure attributes (transport, sanitation, signage).
    • H2: Domestic and foreign tourists differ significantly in their importance ratings.
    • H3: Destination-image dimensions significantly predict revisit intention.

    Feasibility

    • Access: visitors can be approached at public places near major monuments, bus stands and homestay clusters; permission is taken from local authorities where needed.
    • Language: the questionnaire is prepared in English and Kannada, with Hindi available for north-Indian visitors.
    • Time and cost: two field visits of about five days each in peak season; SPSS through the institute licence.
  3. 1 min

    Problem statement

    Hampi attracts large numbers of domestic and international visitors, but visitor experience depends on many providers — monument management, local transport, accommodation, food outlets, guides and civic services — which rarely share data on what tourists value or where they are disappointed. Online reviews and anecdotal complaints point to problems with local transport, signage, sanitation and information at sites, but there is no systematic evidence on which attributes matter most to visitors and how the destination actually performs on them, or on how domestic and foreign tourists differ.

    Without such evidence, improvement efforts may be spread thinly or directed to attributes visitors do not prioritise. This study therefore measures the importance and performance of Hampi's destination attributes using Importance–Performance Analysis, compares domestic and foreign tourists, and examines how destination image relates to revisit and recommendation intentions, in order to identify clear priorities for destination stakeholders.

  4. 1 min

    Objectives & scope

    1. 01To identify the destination attributes that tourists consider important when visiting Hampi.
    2. 02To measure tourists' perception of Hampi's performance on these attributes.
    3. 03To identify importance–performance gaps and plot the IPA grid.
    4. 04To compare the perceptions of domestic and foreign tourists.
    5. 05To examine the influence of destination-image dimensions on revisit and recommendation intention.
    6. 06To suggest priorities for hotels, tour operators and tourism authorities at Hampi.

    Scope

    In scope

    • Tourists aged 18 and above who have spent at least one full day at Hampi, surveyed at major sites and accommodation clusters.
    • Around 22 cognitive destination-image attributes rated on importance and performance, plus overall satisfaction, revisit and recommend intention.
    • Domestic vs foreign comparison, IPA grid, gap analysis and regression.
    • Secondary context from official tourism statistics, quoted exactly from their published sources.

    Out of scope

    • Residents' attitudes to tourism and economic impact studies.
    • Conservation assessment of monuments.
    • Day trippers staying under a few hours, school groups and pilgrims visiting only for a ritual.
    • Any collection of names, phone numbers, passport or ID details.
  5. 1 min

    Methodology

    Research design

    A descriptive cross-sectional survey with Importance–Performance Analysis.

    Attribute list (22 items, 9 dimensions)

    Heritage and attractions (3) · Natural scenery (2) · Accessibility and local transport (3) · Accommodation (2) · Food and restaurants (2) · Cleanliness and sanitation (3) · Safety and security (2) · Information and interpretation (3) · Local people and value for money (2). Items are drafted from the destination-image literature and refined through 10 short interviews with tourists and 3 with local tour operators.

    Instrument

    • Section A: profile (age group, gender, domestic/foreign, travel party, trip purpose, length of stay, accommodation type, first/repeat visit).
    • Section B: importance of each attribute (1 = not at all important … 5 = extremely important), answered before the performance section.
    • Section C: performance of Hampi on the same attributes (1 = very poor … 5 = excellent).
    • Section D: overall satisfaction, revisit intention and recommend intention (5-point).

    Sample

    • About 300 tourists (target ~200 domestic, ~100 foreign) using quota sampling by origin and systematic intercept at five locations (Virupaksha temple area, Vittala temple complex approach, Royal Enclosure, Hampi bus stand area, and a homestay cluster), on weekdays and weekends.
    • Pilot: 20 tourists.

    Analysis (SPSS + Excel)

    1. Cronbach's alpha for importance and performance sets.
    2. Mean importance and performance per attribute; paired t-test for each gap.
    3. IPA grid in Excel, cross-hairs at the grand means.
    4. Independent t-test domestic vs foreign (Welch's where variances differ).
    5. Multiple regression of revisit intention on dimension performance scores.

    Timeline (14 weeks)

    Weeks 1–3 review and instrument · 4 pilot · 5–8 fieldwork (two visits) · 9–11 analysis · 12–14 writing, presentation and viva.

  6. 1 min

    Architecture & tech stack

    • Structured tourist questionnaire (bilingual, 5-point)
    • Importance–Performance Analysis (Martilla & James)
    • SPSS (t-test, paired t-test, regression, reliability)
    • MS Excel (IPA grid charts)
    • Secondary data: Ministry of Tourism and Karnataka Tourism statistics
    • Google Forms / printed questionnaires

    The study moves from attribute identification to the IPA grid and then to management priorities.

    flowchart TD
      A["Literature on destination image and IPA"] --> B["Attribute pool"]
      C["Interviews: 10 tourists, 3 operators"] --> B
      B --> D["22 attributes, 9 dimensions"]
      D --> E["Bilingual questionnaire: importance + performance"]
      E --> F["Pilot: 20 tourists"]
      F --> G["Fieldwork: ~300 tourists, 5 locations"]
      G --> H["SPSS: reliability, means"]
      H --> I["Paired t-test: gaps"]
      H --> J["IPA grid in Excel"]
      H --> K["Domestic vs foreign t-tests"]
      H --> L["Regression: revisit intention"]
      I --> M[Priorities for stakeholders]
      J --> M
      K --> M
      L --> M

    IPA quadrants

    QuadrantImportancePerformanceAction
    I — Concentrate HereHighLowUrgent improvement
    II — Keep Up the Good WorkHighHighMaintain
    III — Low PriorityLowLowMonitor; limited resources
    IV — Possible OverkillLowHighResources may be redirected

    Cross-hairs are placed at the grand mean of importance and of performance (data-centred IPA), which is the usual choice when most ratings cluster above the scale midpoint.

    Data protection

    No names, contact details or travel-document numbers are collected. Paper forms are coded and entered into SPSS; images of forms are not shared.

  7. 5 modules

    Modules

    • Literature Review and Attribute Development

      Review destination-image and IPA research, draft an attribute pool, refine it through short interviews with tourists and local operators, and finalise 22 attributes across nine dimensions.

    • Questionnaire and Pilot

      Prepare the bilingual questionnaire with separate importance and performance sections, translate and back-translate the Kannada version, pilot it with 20 tourists and revise unclear items.

    • Fieldwork

      Survey about 300 tourists across five locations and both weekdays and weekends, maintain quota counts for domestic and foreign visitors, and keep a field diary of locations, times, refusals and conditions.

    • Statistical Analysis and IPA Grid

      Enter data in SPSS, check reliability, compute attribute means and paired-t gaps, plot the IPA grid in Excel, compare domestic and foreign visitors and run the revisit-intention regression.

    • Secondary Data and Recommendations

      Place findings in the context of official Ministry of Tourism and Karnataka Tourism statistics, then write quadrant-wise recommendations for hotels, homestays, tour operators and local tourism authorities.

  8. Locked

    Presentation

    12 slides with speaker notes. The outline below is free; the bullets, notes and the generated .pptx unlock with the project.

    1. Destination Image of Hampi: An IPA Study
    2. Hampi as a Destination
    3. Problem and Objectives
    4. Concepts
    5. Attributes
    6. Methodology
    7. Reliability and Profile
    8. Importance–Performance Gaps
    9. IPA Grid
    10. Domestic vs Foreign and Revisit Intention
    11. Recommendations
    12. Conclusion and Future Research

    Bullets, speaker notes and the .pptx download unlock with the project.

    Presentation is locked: 12 slides, Speaker notes, .pptx download.

  9. Locked

    How to run

    A research, analysis or design project, so there's no code bundle: 1 step to carry it out with Structured tourist questionnaire (bilingual, 5-point), Importance–Performance Analysis (Martilla & James) and SPSS (t-test, paired t-test, regression, reliability).

    The good part is behind this lock. Like every good viva answer.

    How to run is locked: 1 step.

  10. 1 min

    Future scope

    • Revised IPA using implicit importance derived from regression coefficients rather than self-stated importance.
    • Seasonal comparison — peak winter season versus the summer lean season.
    • Online review mining — coding TripAdvisor and Google review text into the same attribute framework.
    • Stakeholder survey of homestay owners, guides and auto-rickshaw drivers on the same attributes.
    • Comparison across heritage circuits such as Badami–Aihole–Pattadakal.
  11. 6 sources

    References

    1. Martilla, J. A., & James, J. C. (1977). Importance-performance analysis. Journal of Marketing, 41(1), 77–79.
    2. Echtner, C. M., & Ritchie, J. R. B. (1991). The meaning and measurement of destination image. Journal of Tourism Studies, 2(2), 2–12.
    3. Ministry of Tourism, Government of India — India Tourism Statistics (annual publication)
    4. Karnataka Tourism — Department of Tourism, Government of Karnataka
    5. UNESCO World Heritage Centre — Group of Monuments at Hampi
    6. Field, A. Discovering Statistics Using IBM SPSS Statistics, 5th ed. SAGE.

    Cite this bundle

    OnlyProjects. (2026). Destination Image and Revisit Intention at Hampi: An Importance–Performance Analysis of Domestic and Foreign Tourists: MHM Travel & Tourism project bundle [Educational resource]. https://onlyprojects.online/projects/mhm-travel-hampi-destination-image-revisit-intention-ipa-survey

Slides, diagrams & files

12 slides. Titles are free; bullets, speaker notes and the .pptx unlock with the project.

  1. SLIDE 1

    Destination Image of Hampi: An IPA Study

  2. SLIDE 2

    Hampi as a Destination

  3. SLIDE 3

    Problem and Objectives

  4. SLIDE 4

    Concepts

  5. SLIDE 5

    Attributes

  6. SLIDE 6

    Methodology

  7. SLIDE 7

    Reliability and Profile

  8. SLIDE 8

    Importance–Performance Gaps

  9. SLIDE 9

    IPA Grid

  10. SLIDE 10

    Domestic vs Foreign and Revisit Intention

  11. SLIDE 11

    Recommendations

  12. SLIDE 12

    Conclusion and Future Research

Architecture diagram

1
flowchart TD
  A["Literature on destination image and IPA"] --> B["Attribute pool"]
  C["Interviews: 10 tourists, 3 operators"] --> B
  B --> D["22 attributes, 9 dimensions"]
  D --> E["Bilingual questionnaire: importance + performance"]
  E --> F["Pilot: 20 tourists"]
  F --> G["Fieldwork: ~300 tourists, 5 locations"]
  G --> H["SPSS: reliability, means"]
  H --> I["Paired t-test: gaps"]
  H --> J["IPA grid in Excel"]
  H --> K["Domestic vs foreign t-tests"]
  H --> L["Regression: revisit intention"]
  I --> M[Priorities for stakeholders]
  J --> M
  K --> M
  L --> M

Files

Viva questions & answers

3 of 14 questions free. Explain each answer in your own words before you move on.

  1. Concept

    What is destination image?

    Destination image is the set of beliefs, ideas and impressions a tourist holds about a place. It has a cognitive part — beliefs about attributes such as monuments, transport and cleanliness — and an affective part — feelings such as excitement or relaxation. My study measures the cognitive image through 22 attributes.

  2. Concept

    Explain Importance–Performance Analysis.

    IPA, introduced by Martilla and James in 1977, asks respondents to rate how important each attribute is and how well the destination performs on it. Plotting mean importance against mean performance gives four quadrants — Concentrate Here, Keep Up the Good Work, Low Priority and Possible Overkill — which tell managers where to act.

  3. Concept

    Why study revisit intention and not only satisfaction?

    Satisfaction describes how the visit felt, but destinations benefit when visitors return or recommend the place. Revisit and recommend intentions are indicators of destination loyalty, so linking image dimensions to them shows which attributes actually drive future visits.

+11 more questions

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For educational purposes only. Use this bundle to understand how the project works, then build and write your own. Submitting it verbatim is between you, your conscience and your external examiner.