68th AIEST conference, 26-30 August 2018, Treviso, Italy

1. Etymology of hotel names
in Bulgaria
Stanislav Ivanov
Email: stanislav.ivanov@vumk.eu
Web: http://stanislavivanov.com
Fani Dimitrova
Email: fani.dimitrowa@abv.bg
68th AIEST conference, 26-30 August 2018, Treviso, Italy

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Dr. Stanislav Ivanov
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• Professor and Vice Rector (Research), Varna
University of Management, Bulgaria
(http://www.vum.bg)
• Editor-in-chief of the European Journal of
Tourism Research (http://ejtr.vumk.eu)
• CEO of Zangador Ltd. (http://www.zangador.eu)
• Member of AIEST (https://www.aiest.org)

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Fani Dimitrova
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• BA (Hons) International Hospitality Management
graduate, Varna University of Management,
Bulgaria (http://www.vum.bg)

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Content
• Problem statement and literature review
• Methodology
• Findings
• Conclusion
• References and further reading
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What names do hoteliers in
Bulgaria use for their
properties?
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Problem statement & literature review
• Brand name is an important part of branding, both
for destinations and corporations.
• Brand name has an impact on the brand awareness,
discoverability via search engines and the way
people perceive the company/brand (Jack Rofled,
2008; Rutz & Bucklin, 2011; Wänke, Herrmann &
Schaffner, 2007). Hence, the choice of a proper
brand name is an important aspect of the
marketing strategy of a company, including travel,
tourism and hospitality firms.
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Problem statement & literature review
• In a tourist destination context, the names of the
tourist companies in a destination are part of the
local tourism and cultural landscape (Nash, 2016)
which provides the uniqueness, distinction and the
memorability of a destination.
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Problem statement & literature review
• Research on hotel names is very scarce and only a
few publications deal with the topic, probably
because of the difficulty to create a comprehensive
list with the names of accommodation
establishments in a country.
• Nash (2016) analyses the names of 52 Norfolk
Island hotels, while Mihailov (2016) and
Dimitrova-Todorova (2000) investigate the names
of hotels in Bulgaria.
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Problem statement & literature review
• The common ground of these publications is the
qualitative approach to the topic. Hence, these
publications evaluate the linguistic aspects of the
hotel names and disregard the impact of various
property characteristics like category, size, type or
location on the choice of a hotel name.
• In our piece of research we adopt quantitative
approach and aim to identify not only the
categories of hotel names, but the role of various
property characteristics on its name.
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Methodology
• Data were collected in March 2017 from the
consolidated registry of accommodation
establishments in Bulgaria
(http://tourism.egov.bg/registers/Register.aspx),
maintained by the Ministry of Tourism.
• All properties without names or with generic names
(e.g. hotel, guest house) were removed from list.
• The final dataset included 5932 accommodation
establishments.
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Methodology
• The categories of names used by the owners of the
accommodation establishments were developed by
the authors on the basis of the meaning of each
individual name. Over a hundred individual groups
were developed initially which were later
aggregated into 20 groups on the basis of
similarities among groups.
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Methodology
• Sample’s characteristics
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Type of Establishment Frequency Percent
Aparthotel 131 2.2
Apartment(s) 117 2.0
Boarding house 13 0.2
Bungalows 77 1.3
Campsite 20 0.3
Caravan 11 0.2
Cottage 26 0.4
Dwelling house 38 0.6
Family hotel 545 9.2
Guest rooms 358 6.0
Holiday complex 40 0.7
Holiday house 42 0.7
Holiday village 15 0.3
Hostel 29 0.5
Hotel 2111 35.6
House (guest house) 1861 31.4
Hut 121 2.0
Monastery 1 0.0
Motel 31 0.5
Spa hotel 45 0.7
Training centre 2 0.0
Villa(s) 298 5.0
Total 5932 100.0

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Methodology
• Sample’s characteristics
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Category Frequency Percent
1 1902 32.1
2 2185 36.8
3 1425 24.0
4 352 5.9
5 68 1.1
Total 5932 100.0
Capacity Frequency Percent
Up to 50 rooms 5206 87.8
51-100 rooms 331 5.6
101-150 rooms 173 2.9
over 150 rooms 222 3.7
Total 5932 100.0

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Methodology
• Sample’s characteristics
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Type of municipality Frequency Percent
Seaside 1572 26.5
Mountain 2602 43.9
Countryside 491 8.3
Urban 1267 21.4
Total 5932 100.0
Type of settlement Frequency Percent
Seaside 1954 32.9
Mountain 2631 44.4
Countryside 491 8.3
Urban 856 14.4
Total 5932 100.0

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Findings
• Name categories
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Name category Examples
Animals Orlitsa (Eagle), Koncheto (The horse), Mecho uho (Bear’s ear)
Flower/Plant/Tree Kokiche (Snowdrop), Roza (Rose), Oreha (The walnut)
Country/City/Village/Continent/Other geographic area Kiten, Sofia, Havana, Casablanca
Mountain/Mountain peak Vihren, Pirin, Murgavets
Sea/Ocean/River/Lake/Dam Cherno more (Black sea), Byalo more (The Aegean), Maritsa
Nature/Natural phenomena Slantse (Sun), Vodopada (The waterfall), Iceberg
Male names Chicho Tsane (Uncle Tsane), Haji Georgi, Ivan
Female names Diana, Maria, Boryana, Zlatina, Preslava
Family names Stoyanovi, Kehayovi, Andreevi
Gods/Goddesses/Saints/Mythical creatures Gorska Feya (Forest fairy), Tangra, Aida
Colours Byalata kashta (The white house), Zelenata kashta (The green house)
Objects/Materials Diamant (Diamond), Korona (Crown), Stara kotva (Old anchor)
Emotions/Expressions/Experiences/Expectations Tihiat kat (The silent place), Naslada (Enjoyment), Relax
Luxury/Quality Elit (Elite), Dvoretsa (The palace), Elegance, Elegant Lux
Geographical directions North, East, South, West
Locations Mezhdu dva svyata (Between two worlds), Pri vodenitsata (By the
watermill)
Time period/Age Starata kashta (The old house), Vreme (Time), Retro
Typical Bulgarian names Kuker, Nestinarka (Fire dancer), Zmeyuva nevesta (Dragon’s bride)
No specific meaning Fema, Sliok, Behi
Other Strazhite (The guards), Lider (Leader), Minyor (Miner)

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Findings
• Distribution of accommodation establishments by name category
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Name category Frequency Percent
Animals 150 2.5
Flower/Plant/Tree 367 6.2
Country/City/Village/Continent/Other geographic area 636 10.7
Mountain/Mountain peak 165 2.8
Sea/Ocean/River/Lake/Dam 123 2.1
Nature/Natural phenomena 307 5.2
Male names 572 9.6
Female names 1223 20.6
Family names 261 4.4
Gods/Goddesses/Saints/Mythical creatures 230 3.9
Colours 69 1.2
Objects/Materials 140 2.4
Emotions/Expressions/Experiences/Expectations 403 6.8
Luxury/Quality 303 5.1
Geographical directions 20 0.3
Locations 244 4.1
Time period/Age 64 1.1
Typical Bulgarian names 89 1.5
No specific meaning 110 1.9
Other 456 7.7
Total 5932 100.0

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Findings
• Cross-tabulation by name category and type of municipality
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Name Category
Type of Municipality
TotalSeaside Mountain Countryside Urban
Animals 59 54 9 28 150
Flower/Plant/Tree 80 184 21 82 367
Country/City/Village/Continent/Other geographic area 163 235 66 172 636
Mountain/Mountain peak 15 108 5 37 165
Sea/Ocean/River/Lake/Dam 38 37 15 33 123
Nature/Natural phenomena 119 101 17 70 307
Male names 141 271 49 111 572
Female names 319 624 113 167 1223
Family names 64 159 19 19 261
Gods/Goddesses/Saints/Mythical creatures 88 82 11 49 230
Colours 24 25 5 15 69
Objects/Materials 56 43 8 33 140
Emotions/Expressions/Experiences/Expectations 115 163 39 86 403
Luxury/Quality 78 93 19 113 303
Geographical directions 9 5 0 6 20
Locations 57 89 29 69 244
Time period/Age 11 29 9 15 64
Typical Bulgarian names 7 53 7 22 89
No specific meaning 19 57 8 26 110
Other 110 190 42 114 456
Total 1572 2602 491 1267 5932
Pearson Chi-square (N=5932, df=57) 361.547 p<0.000

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Findings
• Cross-tabulation by name category and type of settlement
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Name Category
Type of Settlement
TotalSeaside Mountain Countryside Urban
Animals 73 54 9 14 150
Flower/Plant/Tree 119 185 21 42 367
Country/City/Village/Continent/Other geographic area 200 237 66 133 636
Mountain/Mountain peak 19 109 5 32 165
Sea/Ocean/River/Lake/Dam 43 38 15 27 123
Nature/Natural phenomena 152 101 17 37 307
Male names 172 274 49 77 572
Female names 376 626 113 108 1223
Family names 76 159 19 7 261
Gods/Goddesses/Saints/Mythical creatures 113 84 11 22 230
Colours 29 25 5 10 69
Objects/Materials 67 43 8 22 140
Emotions/Expressions/Experiences/Expectations 127 164 39 73 403
Luxury/Quality 119 98 19 67 303
Geographical directions 10 5 0 5 20
Locations 75 89 29 51 244
Time period/Age 12 30 9 13 64
Typical Bulgarian names 7 53 7 22 89
No specific meaning 28 58 8 16 110
Other 137 199 42 78 456
Total 1954 2631 491 856 5932
Pearson Chi-square (N=5932, df=57) 390.537 p<0.000

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Findings
• Cross-tabulation by name category and star categorization
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Name Category
Category
Total1 star 2 stars 3 stars 4 stars 5 stars
Animals 52 52 32 14 0 150
Flower/Plant/Tree 124 135 81 26 1 367
Country/City/Village/Continent/Other geographic area 182 202 163 73 16 636
Mountain/Mountain peak 46 59 43 14 3 165
Sea/Ocean/River/Lake/Dam 42 40 33 6 2 123
Nature/Natural phenomena 81 114 80 29 3 307
Male names 188 262 108 11 3 572
Female names 448 502 232 34 7 1223
Family names 100 125 36 0 0 261
Gods/Goddesses/Saints/Mythical creatures 53 69 86 20 2 230
Colours 24 24 16 5 0 69
Objects/Materials 45 37 46 10 2 140
Emotions/Expressions/Experiences/Expectations 140 129 110 22 2 403
Luxury/Quality 46 82 104 47 24 303
Geographical directions 6 7 6 1 0 20
Locations 95 79 60 8 2 244
Time period/Age 21 23 19 1 0 64
Typical Bulgarian names 27 44 18 0 0 89
No specific meaning 36 39 32 3 0 110
Other 146 161 120 28 1 456
Total 1902 2185 1425 352 68 5932
Pearson Chi-square (N=5932, df=76) 499.753 p<0.000

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Findings
• Cross-tabulation by name category and capacity
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Name Category
Capacity
Total
Up to 50
rooms
51-100
rooms
101-150
rooms
Over 150
rooms
Animals 123 7 10 10 150
Flower/Plant/Tree 304 34 12 17 367
Country/City/Village/Continent/Other geographic area 490 59 36 51 636
Mountain/Mountain peak 136 15 9 5 165
Sea/Ocean/River/Lake/Dam 100 10 6 7 123
Nature/Natural phenomena 254 25 9 19 307
Male names 555 10 3 4 572
Female names 1148 32 21 22 1223
Family names 261 0 0 0 261
Gods/Goddesses/Saints/Mythical creatures 190 16 13 11 230
Colours 59 7 1 2 69
Objects/Materials 113 11 6 10 140
Emotions/Expressions/Experiences/Expectations 365 17 9 12 403
Luxury/Quality 210 38 18 37 303
Geographical directions 19 1 0 0 20
Locations 218 13 10 3 244
Time period/Age 62 2 0 0 64
Typical Bulgarian names 86 2 0 1 89
No specific meaning 107 2 1 0 110
Other 406 30 9 11 456
Total 5206 331 173 222 5932
Pearson Chi-square (N=5932, df=57) 401.764 p<0.000

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Findings
• Cross-tabulation by name category and type of establishment
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Conclusion
From a destination management perspective:
• The names of accommodation establishments are
very diverse, but are heavily concentrated in a few
categories only: female, male and family names
constitute 34.6% of all names, and geographic
toponyms 10.6%.
• Most of the names are typical Bulgarian words,
which appeal to domestic tourists and contribute to
the distinctive cultural and linguistic landscape of
the destination, but are difficult to translate and
understand by international tourists.
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References and further reading
• Dimitrova-Todorova, L. (2000). Names of Hotels and Restaurants in Sofia. Polish onomastics and new
linguistic directions. Materials from XI National Onomastic Conference 15-17 June 1998. Bydgoszcz:
Wydaw. University WSP, 2000, pp. 133-142.
• Jack Rotfeld, H. (2008). Brand image of company names matters in ways that can't be ignored. Journal
of Product & Brand Management, 17(2), 121-122.
• Malenkina, N., & Ivanov, S. (2018). A Linguistic Analysis of the Official Tourism Websites of the
Seventeen Spanish Autonomous Communities. Journal of Destination Marketing & Management, 9,
204-233
• Mihailov, P. (2016). The Names of the Hotels: Between the Onomastics and the Tourist Science.
Plovdiv: Intelexpert – 94.
• Morgan, N., Pritchard, A. and Pride, R. (Eds.) (2004). Destination Branding: Creating the Unique
Destination Proposition. Oxford: Butterworth-Heinemann
• Morrison, A. (2013). Marketing and Managing Tourism Destinations. London: Routledge.
• Nash, J. (2016). May I Have Your Name Please? Norfolk Island Hotel Names. Tourism Analysis, 21(5),
541-547.
• Rutz, O. J., & Bucklin, R. E. (2011). From generic to branded: A model of spillover in paid search
advertising. Journal of Marketing Research, 48(1), 87-102.
• Wänke, M., Herrmann, A., & Schaffner, D. (2007). Brand name influence on brand perception.
Psychology & Marketing, 24(1), 1-24.
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This presentation is developed within the frame of
Project BG05M2OP001-1.002-0008-C01 “Centre for
Competence and Intelligent Solutions for the Creative
and Recreational Industries (INCREA)”. The project has
been funded within Operational Programme “Science
and Education for Smart Growth (2014-2020)” and with
support from the European Commission. The
presentation reflects the views only of the authors and
the Commission cannot be held responsible for any use
which may be made of the information contained
therein.

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