Response ID
Last page
Seed
Name
Sex/Gender
Age
Holiday_packages_1...7
Holiday_packages_1...8
Holiday_packages_1...9
Holiday_packages_2...10
Holiday_packages_2...11
Holiday_packages_2...12
Holiday_packages_3...13
Holiday_packages_3...14
Holiday_packages_3...15
Holiday_packages_4...16
Holiday_packages_4...17
Holiday_packages_4...18
Holiday_packages_5...19
Holiday_packages_5...20
Holiday_packages_5...21
Holiday_packages_6...22
Holiday_packages_6...23
Holiday_packages_6...24
Holiday_packages_7...25
Holiday_packages_7...26
Holiday_packages_7...27
Holiday_packages_8...28
Holiday_packages_8...29
Holiday_packages_8...30
Holiday_packages_9...31
Holiday_packages_9...32
Holiday_packages_9...33
Holiday_packages_10...34
Holiday_packages_10...35
Holiday_packages_10...36
Holiday_packages_11...37
Holiday_packages_11...38
Holiday_packages_11...39
Holiday_packages_12...40
Holiday_packages_12...41
1
10
14
51187278
Claudio
Male
18-28
Choice_Set_1_Option_2
Choice_Set_1_Option_1
Choice_Set_1_Option_3
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_3_Option_2
Choice_Set_3_Option_1
Choice_Set_3_Option_3
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_4_Option_1
Choice_Set_5_Option_2
Choice_Set_5_Option_1
Choice_Set_5_Option_3
Choice_Set_6_Option_2
Choice_Set_6_Option_1
Choice_Set_6_Option_3
Choice_Set_7_Option_2
Choice_Set_7_Option_1
Choice_Set_7_Option_3
Choice_Set_8_Option_3
Choice_Set_8_Option_1
Choice_Set_8_Option_2
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_9_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_1
Choice_Set_10_Option_3
Choice_Set_11_Option_2
Choice_Set_11_Option_1
Choice_Set_11_Option_3
Choice_Set_12_Option_2
Choice_Set_12_Option_1
2
17
14
2048659550
Donato
Male
18-28
Choice_Set_1_Option_1
Choice_Set_1_Option_2
Choice_Set_1_Option_3
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_3_Option_3
Choice_Set_3_Option_2
Choice_Set_3_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_4_Option_1
Choice_Set_5_Option_2
Choice_Set_5_Option_1
Choice_Set_5_Option_3
Choice_Set_6_Option_1
Choice_Set_6_Option_2
Choice_Set_6_Option_3
Choice_Set_7_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_8_Option_1
Choice_Set_9_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_10_Option_3
Choice_Set_10_Option_2
Choice_Set_10_Option_1
Choice_Set_11_Option_2
Choice_Set_11_Option_1
Choice_Set_11_Option_3
Choice_Set_12_Option_1
Choice_Set_12_Option_2
3
19
14
141315052
NA
Male
18-28
Choice_Set_1_Option_3
Choice_Set_1_Option_2
Choice_Set_1_Option_1
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_3_Option_3
Choice_Set_3_Option_2
Choice_Set_3_Option_1
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_3
Choice_Set_5_Option_2
Choice_Set_5_Option_1
Choice_Set_6_Option_3
Choice_Set_6_Option_2
Choice_Set_6_Option_1
Choice_Set_7_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_8_Option_3
Choice_Set_8_Option_2
Choice_Set_8_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_9_Option_1
Choice_Set_10_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_11_Option_3
Choice_Set_11_Option_2
Choice_Set_11_Option_1
Choice_Set_12_Option_2
Choice_Set_12_Option_1
4
26
14
2057100721
Val Vargas
Female
18-28
Choice_Set_1_Option_3
Choice_Set_1_Option_2
Choice_Set_1_Option_1
Choice_Set_2_Option_2
Choice_Set_2_Option_3
Choice_Set_2_Option_1
Choice_Set_3_Option_2
Choice_Set_3_Option_1
Choice_Set_3_Option_3
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_3
Choice_Set_5_Option_1
Choice_Set_5_Option_2
Choice_Set_6_Option_3
Choice_Set_6_Option_2
Choice_Set_6_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_7_Option_1
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_8_Option_1
Choice_Set_9_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_11_Option_1
Choice_Set_11_Option_2
Choice_Set_11_Option_3
Choice_Set_12_Option_2
Choice_Set_12_Option_1
5
28
14
699559996
Tommaso
Male
18-28
Choice_Set_1_Option_1
Choice_Set_1_Option_3
Choice_Set_1_Option_2
Choice_Set_2_Option_3
Choice_Set_2_Option_1
Choice_Set_2_Option_2
Choice_Set_3_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_2
Choice_Set_5_Option_1
Choice_Set_5_Option_3
Choice_Set_6_Option_3
Choice_Set_6_Option_1
Choice_Set_6_Option_2
Choice_Set_7_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_8_Option_1
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_9_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_3
Choice_Set_10_Option_2
Choice_Set_11_Option_2
Choice_Set_11_Option_3
Choice_Set_11_Option_1
Choice_Set_12_Option_2
Choice_Set_12_Option_1
6
29
14
1398375619
Clelia
Female
18-28
Choice_Set_1_Option_2
Choice_Set_1_Option_3
Choice_Set_1_Option_1
Choice_Set_2_Option_3
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_3_Option_3
Choice_Set_3_Option_2
Choice_Set_3_Option_1
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_2
Choice_Set_5_Option_3
Choice_Set_5_Option_1
Choice_Set_6_Option_3
Choice_Set_6_Option_2
Choice_Set_6_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_7_Option_1
Choice_Set_8_Option_3
Choice_Set_8_Option_2
Choice_Set_8_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_9_Option_1
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_11_Option_2
Choice_Set_11_Option_1
Choice_Set_11_Option_3
Choice_Set_12_Option_2
Choice_Set_12_Option_1
7
37
14
1363179014
NA
Male
40-50
Choice_Set_1_Option_1
Choice_Set_1_Option_3
Choice_Set_1_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_2_Option_2
Choice_Set_3_Option_1
Choice_Set_3_Option_3
Choice_Set_3_Option_2
Choice_Set_4_Option_1
Choice_Set_4_Option_3
Choice_Set_4_Option_2
Choice_Set_5_Option_3
Choice_Set_5_Option_2
Choice_Set_5_Option_1
Choice_Set_6_Option_2
Choice_Set_6_Option_3
Choice_Set_6_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_7_Option_1
Choice_Set_8_Option_3
Choice_Set_8_Option_2
Choice_Set_8_Option_1
Choice_Set_9_Option_1
Choice_Set_9_Option_3
Choice_Set_9_Option_2
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_11_Option_2
Choice_Set_11_Option_1
Choice_Set_11_Option_3
Choice_Set_12_Option_2
Choice_Set_12_Option_1
8
38
14
1458312278
Derek
Male
18-28
Choice_Set_1_Option_3
Choice_Set_1_Option_1
Choice_Set_1_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_2
Choice_Set_2_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_3_Option_3
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_1
Choice_Set_5_Option_2
Choice_Set_5_Option_3
Choice_Set_6_Option_1
Choice_Set_6_Option_2
Choice_Set_6_Option_3
Choice_Set_7_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_8_Option_1
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_9_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_11_Option_1
Choice_Set_11_Option_2
Choice_Set_11_Option_3
Choice_Set_12_Option_1
Choice_Set_12_Option_2
9
39
14
1074892730
Luca
Male
18-28
Choice_Set_1_Option_2
Choice_Set_1_Option_1
Choice_Set_1_Option_3
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_3_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_3
Choice_Set_5_Option_1
Choice_Set_5_Option_2
Choice_Set_6_Option_2
Choice_Set_6_Option_3
Choice_Set_6_Option_1
Choice_Set_7_Option_3
Choice_Set_7_Option_2
Choice_Set_7_Option_1
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_8_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_9_Option_1
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_11_Option_3
Choice_Set_11_Option_1
Choice_Set_11_Option_2
Choice_Set_12_Option_2
Choice_Set_12_Option_1
10
41
14
390647867
NA
Male
29-39
Choice_Set_1_Option_1
Choice_Set_1_Option_2
Choice_Set_1_Option_3
Choice_Set_2_Option_1
Choice_Set_2_Option_2
Choice_Set_2_Option_3
Choice_Set_3_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_4_Option_3
Choice_Set_4_Option_2
Choice_Set_4_Option_1
Choice_Set_5_Option_2
Choice_Set_5_Option_3
Choice_Set_5_Option_1
Choice_Set_6_Option_3
Choice_Set_6_Option_1
Choice_Set_6_Option_2
Choice_Set_7_Option_1
Choice_Set_7_Option_3
Choice_Set_7_Option_2
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_8_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_1
Choice_Set_9_Option_3
Choice_Set_10_Option_3
Choice_Set_10_Option_2
Choice_Set_10_Option_1
Choice_Set_11_Option_3
Choice_Set_11_Option_1
Choice_Set_11_Option_2
Choice_Set_12_Option_2
Choice_Set_12_Option_1
11
43
14
1706585502
NA
Female
18-28
Choice_Set_1_Option_1
Choice_Set_1_Option_3
Choice_Set_1_Option_2
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_3_Option_3
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_3
Choice_Set_5_Option_2
Choice_Set_5_Option_1
Choice_Set_6_Option_3
Choice_Set_6_Option_2
Choice_Set_6_Option_1
Choice_Set_7_Option_3
Choice_Set_7_Option_2
Choice_Set_7_Option_1
Choice_Set_8_Option_2
Choice_Set_8_Option_1
Choice_Set_8_Option_3
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_9_Option_1
Choice_Set_10_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_11_Option_2
Choice_Set_11_Option_3
Choice_Set_11_Option_1
Choice_Set_12_Option_1
Choice_Set_12_Option_2
12
47
14
1285942136
Veronica
Female
18-28
Choice_Set_1_Option_3
Choice_Set_1_Option_1
Choice_Set_1_Option_2
Choice_Set_2_Option_3
Choice_Set_2_Option_1
Choice_Set_2_Option_2
Choice_Set_3_Option_2
Choice_Set_3_Option_1
Choice_Set_3_Option_3
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_4_Option_1
Choice_Set_5_Option_1
Choice_Set_5_Option_3
Choice_Set_5_Option_2
Choice_Set_6_Option_3
Choice_Set_6_Option_2
Choice_Set_6_Option_1
Choice_Set_7_Option_1
Choice_Set_7_Option_3
Choice_Set_7_Option_2
Choice_Set_8_Option_3
Choice_Set_8_Option_2
Choice_Set_8_Option_1
Choice_Set_9_Option_1
Choice_Set_9_Option_3
Choice_Set_9_Option_2
Choice_Set_10_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_11_Option_1
Choice_Set_11_Option_3
Choice_Set_11_Option_2
Choice_Set_12_Option_1
Choice_Set_12_Option_2
13
48
14
1761483526
Giorgia
Female
18-28
Choice_Set_1_Option_1
Choice_Set_1_Option_2
Choice_Set_1_Option_3
Choice_Set_2_Option_2
Choice_Set_2_Option_1
Choice_Set_2_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_3_Option_3
Choice_Set_4_Option_1
Choice_Set_4_Option_3
Choice_Set_4_Option_2
Choice_Set_5_Option_2
Choice_Set_5_Option_3
Choice_Set_5_Option_1
Choice_Set_6_Option_2
Choice_Set_6_Option_3
Choice_Set_6_Option_1
Choice_Set_7_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_8_Option_3
Choice_Set_8_Option_2
Choice_Set_8_Option_1
Choice_Set_9_Option_1
Choice_Set_9_Option_3
Choice_Set_9_Option_2
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_10_Option_1
Choice_Set_11_Option_3
Choice_Set_11_Option_2
Choice_Set_11_Option_1
Choice_Set_12_Option_2
Choice_Set_12_Option_1   . 	
Attribute
Choice_Set_1_Option_1
Choice_Set_1_Option_2
Choice_Set_1_Option_3
Choice_Set_2_Option_1
Choice_Set_2_Option_2
Choice_Set_2_Option_3
Choice_Set_3_Option_1
Choice_Set_3_Option_2
Choice_Set_3_Option_3
Choice_Set_4_Option_1
Choice_Set_4_Option_2
Choice_Set_4_Option_3
Choice_Set_5_Option_1
Choice_Set_5_Option_2
Choice_Set_5_Option_3
Choice_Set_6_Option_1
Choice_Set_6_Option_2
Choice_Set_6_Option_3
Choice_Set_7_Option_1
Choice_Set_7_Option_2
Choice_Set_7_Option_3
Choice_Set_8_Option_1
Choice_Set_8_Option_2
Choice_Set_8_Option_3
Choice_Set_9_Option_1
Choice_Set_9_Option_2
Choice_Set_9_Option_3
Choice_Set_10_Option_1
Choice_Set_10_Option_2
Choice_Set_10_Option_3
Choice_Set_11_Option_1
Choice_Set_11_Option_2
Choice_Set_11_Option_3
Choice_Set_12_Option_1
Choice_Set_12_Option_2
1
Continent Choice
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
Asia
America
Europe
2
Vacation Type
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Urban Adventures
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
Cultural and Historical Visits
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Urban Adventures
Adventure and Nature Explorations
Cultural and Historical Visits
Urban Adventures
Adventure and Nature Explorations
3
Budget Level
2,000 EUR
6,000 EUR
4,000 EUR
4,000 EUR
2,000 EUR
6,000 EUR
6,000 EUR
4,000 EUR
2,000 EUR
8,000 EUR
10,000 EUR
12,000 EUR
10,000 EUR
12,000 EUR
8,000 EUR
12,000 EUR
8,000 EUR
10,000 EUR
8,000 EUR
10,000 EUR
12,000 EUR
10,000 EUR
12,000 EUR
8,000 EUR
12,000 EUR
8,000 EUR
10,000 EUR
2,000 EUR
6,000 EUR
4,000 EUR
4,000 EUR
2,000 EUR
6,000 EUR
6,000 EUR
4,000 EUR
4
Trip Duration
Short Break (up to 1 week)
Extended Stay (more than 3 weeks)
Extended Stay (more than 3 weeks)
Short Break (up to 1 week)
Medium Getaway (1 to 3 weeks)
Short Break (up to 1 week)
Medium Getaway (1 to 3 weeks)
Medium Getaway (1 to 3 weeks)
Extended Stay (more than 3 weeks)
Extended Stay (more than 3 weeks)
Short Break (up to 1 week)
Short Break (up to 1 week)
Extended Stay (more than 3 weeks)
Extended Stay (more than 3 weeks)
Medium Getaway (1 to 3 weeks)
Medium Getaway (1 to 3 weeks)
Short Break (up to 1 week)
Medium Getaway (1 to 3 weeks)
Medium Getaway (1 to 3 weeks)
Medium Getaway (1 to 3 weeks)
Short Break (up to 1 week)
Extended Stay (more than 3 weeks)
Medium Getaway (1 to 3 weeks)
Extended Stay (more than 3 weeks)
Extended Stay (more than 3 weeks)
Short Break (up to 1 week)
Short Break (up to 1 week)
Medium Getaway (1 to 3 weeks)
Extended Stay (more than 3 weeks)
Medium Getaway (1 to 3 weeks)
Short Break (up to 1 week)
Short Break (up to 1 week)
Medium Getaway (1 to 3 weeks)
Short Break (up to 1 week)
Extended Stay (more than 3 weeks)
5
Climate Preference
Tropical
Cold
Temperate
Temperate
Tropical
Cold
Tropical
Cold
Temperate
Temperate
Tropical
Cold
Cold
Temperate
Tropical
Cold
Temperate
Tropical
Cold
Temperate
Tropical
Cold
Temperate
Tropical
Tropical
Cold
Temperate
Temperate
Tropical
Cold
Tropical
Cold
Temperate
Temperate
Tropical
6
Activity Types
Outdoor Activities (hiking, skiing, etc.)
Water Activities (diving, sailing, etc.)
Outdoor Activities (hiking, skiing, etc.)
Water Activities (diving, sailing, etc.)
Water Activities (diving, sailing, etc.)
Educational Activities (museums, tours)
Outdoor Activities (hiking, skiing, etc.)
Educational Activities (museums, tours)
Educational Activities (museums, tours)
Water Activities (diving, sailing, etc.)
Outdoor Activities (hiking, skiing, etc.)
Water Activities (diving, sailing, etc.)
Educational Activities (museums, tours)
Outdoor Activities (hiking, skiing, etc.)
Outdoor Activities (hiking, skiing, etc.)
Educational Activities (museums, tours)
Educational Activities (museums, tours)
Water Activities (diving, sailing, etc.)
Water Activities (diving, sailing, etc.)
Educational Activities (museums, tours)
Educational Activities (museums, tours)
Outdoor Activities (hiking, skiing, etc.)
Outdoor Activities (hiking, skiing, etc.)
Educational Activities (museums, tours)
Water Activities (diving, sailing, etc.)
Outdoor Activities (hiking, skiing, etc.)
Water Activities (diving, sailing, etc.)
Educational Activities (museums, tours)
Educational Activities (museums, tours)
Outdoor Activities (hiking, skiing, etc.)
Educational Activities (museums, tours)
Water Activities (diving, sailing, etc.)
Water Activities (diving, sailing, etc.)
Outdoor Activities (hiking, skiing, etc.)
Water Activities (diving, sailing, etc.)
7
Accommodation Preferences
Hotels
Hostels
Camping
Hostels
Camping
Hotels
Camping
Hotels
Hostels
Hotels
Hostels
Camping
Camping
Hotels
Hostels
Hostels
Camping
Hotels
Hostels
Camping
Hotels
Hotels
Hostels
Camping
Camping
Hotels
Hostels
Hotels
Hostels
Camping
Hostels
Camping
Hotels
Camping
Hotels
8
Travel Timing
Peak Season
Peak Season
Shoulder Season
Off-Peak Season
Shoulder Season
Shoulder Season
Off-Peak Season
Peak Season
Off-Peak Season
Shoulder Season
Shoulder Season
Peak Season
Peak Season
Off-Peak Season
Peak Season
Shoulder Season
Off-Peak Season
Off-Peak Season
Off-Peak Season
Shoulder Season
Off-Peak Season
Off-Peak Season
Peak Season
Peak Season
Shoulder Season
Shoulder Season
Peak Season
Peak Season
Off-Peak Season
Off-Peak Season
Shoulder Season
Off-Peak Season
Shoulder Season
Peak Season
Peak Season
9
Airline Type
Low-Cost Carrier
Charter Flights
Regional Airlines
Charter Flights
Regional Airlines
Low-Cost Carrier
Charter Flights
Regional Airlines
Low-Cost Carrier
Regional Airlines
Low-Cost Carrier
Charter Flights
Low-Cost Carrier
Charter Flights
Regional Airlines
Regional Airlines
Low-Cost Carrier
Charter Flights
Low-Cost Carrier
Charter Flights
Regional Airlines
Regional Airlines
Low-Cost Carrier
Charter Flights
Low-Cost Carrier
Charter Flights
Regional Airlines
Charter Flights
Regional Airlines
Low-Cost Carrier
Charter Flights
Regional Airlines
Low-Cost Carrier
Regional Airlines
Low-Cost Carrier.    43
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some. replace this code: 
# Create the choice_id variable
merged_df <- merged_df %>%
  mutate(choice_id = paste(Respondent_ID, Choice_Set, sep = "_"))

# Center and scale the Price variable if needed
merged_df <- merged_df %>%
  mutate(Price_scaled = scale(Price))

# Merge the willingness to pay data
merged_df <- merged_df %>%
  left_join(willingness_to_pay, by = c("Respondent_ID", "Choice_Set"))

# Ensure Buy_Option is a factor with appropriate levels
merged_df$Buy_Option <- factor(merged_df$Buy_Option, levels = c("none", "some", "any"))

# Manually handle non-numeric values and convert to numeric
merged_df <- merged_df %>%
  mutate(
    Usage = case_when(
      Usage == "New" ~ 0,
      Usage == "Used" ~ 1,
      TRUE ~ NA_real_
    ),
    Material = case_when(
      Material == "Not recyclable" ~ 0,
      Material == "50% recyclable" ~ 1,
      Material == "100% recyclable" ~ 2,
      TRUE ~ NA_real_
    ),
    Durability = case_when(
      Durability == "6 months to 1 year" ~ 1,
      Durability == "1 to 2 years" ~ 2,
      Durability == "More than 2 years" ~ 3,
      TRUE ~ NA_real_
    ),
    `Production Location` = case_when(
      `Production Location` == "Local" ~ 1,
      `Production Location` == "Europe" ~ 2,
      `Production Location` == "Intercontinental" ~ 3,
      TRUE ~ NA_real_
    ),
    `Brand Reputation` = case_when(
      `Brand Reputation` == "Ethical brand" ~ 1,
      `Brand Reputation` == "Mainstream brand" ~ 2,
      `Brand Reputation` == "Luxury brand" ~ 3,
      TRUE ~ NA_real_
    ),
    `Marketing Approach` = case_when(
      `Marketing Approach` == "Wear Green, Think Green - Commit to a Cleaner Planet with Our Clothes" ~ 1,
      `Marketing Approach` == "Style that Speaks - Exclusive Designs That Only We Offer" ~ 2,
      `Marketing Approach` == "Get More for Less - The Best Style at the Best Price" ~ 3,
      TRUE ~ NA_real_
    ),
    Fit = case_when(
      Fit == "Regular fit" ~ 1,
      Fit == "Slim fit" ~ 2,
      Fit == "Loose fit" ~ 3,
      TRUE ~ NA_real_
    ),
    Design = case_when(
      Design == "Jeans" ~ 1,
      Design == "Sweatpants" ~ 2,
      Design == "Suit Pants" ~ 3,
      TRUE ~ NA_real_
    )
  )

# Drop rows with any remaining NA values in columns of interest
merged_df <- merged_df %>%
  drop_na(Usage, Material, Durability, `Production Location`, `Brand Reputation`, `Marketing Approach`, Fit, Design)

# Prepare data for mlogit
mlogit_data <- mlogit.data(merged_df, choice = "Preference", shape = "long", 
                           id.var = "Respondent_ID", chid.var = "choice_id")

# Fit the model excluding variables causing multicollinearity issues
mnl_model_with_price <- mlogit(Preference ~ 0 + factor(Usage) + factor(Material) + factor(Durability) + factor(`Production Location`) + factor(`Brand Reputation`) +
                                 factor(`Marketing Approach`) + factor(Fit) + factor(Design) + Price_scaled, 
                               data = mlogit_data)

# Extract coefficients and confidence intervals for the final model with Price
coef_summary_with_price <- tidy(mnl_model_with_price, conf.int = TRUE)

# Recode factors back to their original levels
coef_summary_with_price <- coef_summary_with_price %>%
  mutate(term = case_when(
    term == "factor(Usage)1" ~ "Usage: Used",
    term == "factor(Material)1" ~ "Material: 50% recyclable",
    term == "factor(Material)2" ~ "Material: 100% recyclable",
    term == "factor(Durability)1" ~ "Durability: 6 months to 1 year",
    term == "factor(Durability)2" ~ "Durability: 1 to 2 years",
    term == "factor(Durability)3" ~ "Durability: More than 2 years",
    term == "factor(`Production Location`)1" ~ "Production Location: Local",
    term == "factor(`Production Location`)2" ~ "Production Location: Europe",
    term == "factor(`Production Location`)3" ~ "Production Location: Intercontinental",
    term == "factor(`Brand Reputation`)1" ~ "Brand Reputation: Ethical brand",
    term == "factor(`Brand Reputation`)2" ~ "Brand Reputation: Mainstream brand",
    term == "factor(`Brand Reputation`)3" ~ "Brand Reputation: Luxury brand",
    term == "factor(`Marketing Approach`)1" ~ "Marketing Approach: Wear Green, Think Green - Commit to a Cleaner Planet with Our Clothes",
    term == "factor(`Marketing Approach`)2" ~ "Marketing Approach: Style that Speaks - Exclusive Designs That Only We Offer",
    term == "factor(`Marketing Approach`)3" ~ "Marketing Approach: Get More for Less - The Best Style at the Best Price",
    term == "factor(Fit)1" ~ "Fit: Regular fit",
    term == "factor(Fit)2" ~ "Fit: Slim fit",
    term == "factor(Fit)3" ~ "Fit: Loose fit",
    term == "factor(Design)1" ~ "Design: Jeans",
    term == "factor(Design)2" ~ "Design: Sweatpants",
    term == "factor(Design)3" ~ "Design: Suit Pants",
    TRUE ~ term
  ))

# Plot the coefficients
mnl_plot <- ggplot(coef_summary_with_price, aes(x = estimate, y = factor(term, levels = rev(unique(term))))) +
  geom_point() +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high), height = 0.2) +
  labs(title = "MNL Coefficients with Confidence Intervals",
       x = "Coefficient Estimate", y = "Attributes") +
  theme_minimal()

# Extract price coefficient
price_coef <- coef(mnl_model_with_price)["Price_scaled"]

# Compute WTP for each attribute level
wtp_summary <- coef_summary_with_price %>%
  filter(term != "Price_scaled") %>%
  mutate(estimate = estimate / -price_coef,
         conf.low = conf.low / -price_coef,
         conf.high = conf.high / -price_coef)

# Plot the WTP
wtp_plot <- ggplot(wtp_summary, aes(x = estimate, y = factor(term, levels = rev(unique(term))))) +
  geom_point() +
  geom_errorbarh(aes(xmin = conf.low, xmax = conf.high), height = 0.2) +
  labs(title = "Willingness to Pay (WTP) with Confidence Intervals",
       x = "WTP", y = "Attributes") +
  theme_minimal()

print(mnl_plot)
print(wtp_plot)