investigation of the revenue management practices of accommodation establishments in turkey: an...

Investigation of the revenue

management practices of

accommodation establishments

in Turkey: An exploratory study

Stanislav Ivanov

and

Çağakan Ayas

The Authors

Çağakan Ayas • BA (Hons) International Hospitality Management

graduate, Varna University of Management, Bulgaria / Cardiff Metropolitan University, UK

2

The Authors

Stanislav Ivanov

• CEO of Zangador Ltd. (http://www.zangador.eu)

3

• Editor-in-chief of the European Journal of Tourism Research (http://ejtr.vumk.eu)

• Vice Rector for Academic Affairs and Research at VUM, Bulgaria(http://www.vumk.eu)

http://www.zangador.eu/

http://ejtr.vumk.eu/

http://www.vumk.eu/

Content

• Introduction

• Brief review of related literature

• Methodology

• Discussion of results

• Conclusion

• References

4

IntroductionBackground

• Huge growth of RM research in the last 25 years, (Anderson and Xie, 2010; Cross et al., 2009; Hayes and Miller, 2011; Ingold et al., 2001; Kimes, 2011; Legoherel et al., 2013; Mauri, 2012; Tranter et al., 2008; Wang et al., 2015; Yeoman and McMahon-Beattie, 2004, 2011) mostly focused on hotel industries in developed economies.

• Research on the application of hotel RM in Central and Eastern Europe, Middle East, Latin America and Africa is scarce (Emeksiz et al., 2006; Gehrels and Blanar, 2012; Güler, 2012; Ivanov, 2014)

5

IntroductionAim

• This exploratory research paper aims at partially filling this gap by focusing on the application of various RM practices by the accommodation establishments in Turkey.

• It provides reality check by looking at whether the theoretical concepts in the field of hotel revenue management have found their ways into the actual business practices of the accommodation establishments in the country.

6

Brief review of related literatureHotel RM system

7

Booking request

RM process

Booking elements

Data and information

Revenue centres

RM software RM tools

Structural elements

Hotel revenue management system

Macroenvironment

Microenvironment

Impacts

Internal environment

Patronage intentions

Customer

RM team

Perceptions of RM fairness

Ivanov & Zhechev(2012)

Brief review of related literatureHotel RM centres

• The RM centres are those departments in the hotel that generate revenues.

• Usually research focuses on a single hotel RM centre or related hospitality industries like restaurants (Heo, 2013; Kimes & Thompson, 2004), casinos (Kuyumcu, 2002), function rooms (Orkin, 2003), golf courses (Rasekh & Li, 2011), spa centres (Kimes & Singh, 2009)

• Recent publications have advocated on total hotel revenue management (Buckhiester, 2012; Wang et al., 2015) that takes into consideration all the revenues generated from the customer, not only the revenues from the rooms.

8

Brief review of related literatureHotel RM tools

• The RM tools include a variety of instruments used by hoteliers to manage demand and supply.

• Pricing tools: price discrimination (Mauri, 2012; Shy, 2008; Tranter et al., 2008), dynamic pricing/early bird/last minute offers (Abrate et al., 2012; Chen and Schwartz, 2013; Schwartz, 2008), rate parity (Demirciftci et al., 2010; Haynes and Egan, 2015; Maier, 2011; 2013), lowest price guarantee (Carvell & Quan, 2008; Demirciftci et al., 2010) and price framing and discounting (Croes and Semrad,

2012).

9

Brief review of related literatureHotel RM tools

• Non-pricing tools: inventory management (overbooking and overcontracting: Hwang and Wen, 2009; Ivanov, 2006, 2015; Koide & Ishii, 2005; Netessine & Shumsky, 2002), room availability guarantee, length-of-stay control (Vinod, 2004), 100% satisfaction guarantee.

• Combined tools: channel management (Choi & Kimes, 2002; Hadjinicola & Panayi, 1997) and optimal room-rate allocation (El Gayar et al., 2011; Guadix et al., 2010).

• Proper channel management needed to avoid conflicts with the distributors (Ivanov et al., 2015) and channel cannibalisation (Ivanov, 2007).

• Non-pricing and combined RM tools are underresearched and provide numerous future research opportunities.

10

Brief review of related literatureHotel RM process

• The RM process is the set and sequences of actions undertaken by revenue managers on strategic, tactical and operational level in relation to managing the revenues of the hotel (Ivanov, 2014: 34).

• Emeksiz et al. (2006) stages: preparation, supply and demand analysis, implementation of RM strategies, evaluation of RM activities and monitoring and amendment of the RM strategy.

• Tranter et al. (2008) steps – customer knowledge, market segmentation and selection, internal assessment, competitive analysis, demand forecasting, channel analysis and selection, dynamic value-based pricing, and channel and inventory management.

11


12

Ivanov & Zhechev(2012)

Goals

Monitoring

Implementation

Forecasting

Analysis

Information

Stage Content

RM metrics – RevPAR, ADR, occupancy, GOPPARStrategic, tactical and operational goals

Operational data and information provided by company’s marketing information system

Analysis of demand and supply in the destination/segmentAnalysis of operational data and information

Forecasting demand and supply in the destination/segmentForecasting RM metrics on a daily basisForecasting methods

Pricing and non pricing RM toolsOptimization processApproaches for solving RM mathematical problems

Performance evaluation of taken decisions and the RM system as a whole

Decision

Sales techniquesHuman resource training


• Data on various statistics and performance metrics (occupancy, ADR, RevPAR, GOPPAR, etc.). Big data analytics is one of the major challenges faced by revenue management because it allows better forecasting and thus better managerial decision (Wang et al., 2015).

• Forecasting is essential for the proper managerial decisions and various historical (time series), advance booking (additive and multiplicative pick up) models, combined (regression, neural networks) and qualitative (Delphi) methods are used (Chen and Kachani; 2007; Frechtling, 2001; Ivanov, 2014; Lim et al., 2009; Phumchusri & Mongkolkul, 2012; Weatherford & Kimes, 2003).

13

Brief review of related literatureHotel RM team and software

• Human resources are an essential factor in the planning and design of the RM system and the proper implementation of the RM process (Aubke et al., 2014; Beck et al., 2011; Selmi & Dornier, 2011; Zarraga-Oberty & Bonache, 2007).

• Their actions actually determine whether the RM system in the hotel is successful and contributes positively to the bottom line of the property.

• Although currently the RM software (Emeksiz et al., 2006; Okumus, 2004) allows the automation of many decisions in the RM process, especially related to pricing and overbooking, it is actually the revenue managers who often need to confirm these decisions and take the responsibility for them.

14

Empirical setting

• In 2014 Turkey had 3131 accommodation establishments with 807316 beds that generated over 130 mln. overnights (Ministry of Culture and Tourism, 2015a, b);

• 2430 (77.61%) of them with 671280 beds (83.15%) were classified as hotels.

• High category establishments prevail: 1270 establishments (constituting 49.30% of the categorised properties (hotels, holiday villages, thermal hotels and thermal holiday villages) or 40.56% of all properties) and 612940 of the beds (81.05% of the beds in categorised properties or 75.92% of all beds) were categorised with 4 or 5 stars.

• In 2014 the 4- and 5-star hotels generated 69.28% of all overnights in accommodation establishments in Turkey.

15

MethodologyResearch questions (1)

RQ1: Revenue centres in the hotels

• RQ1.1: Which are the revenue centres of hotels in Turkey?

• RQ1.2: Which revenue centres have greatest potential for development?

RQ2: Pricing and non-pricing revenue management tools and sales techniques

• RQ2.1: What is the level of application of the revenue management tools by hoteliers in Turkey?

• RQ2.2: What is the perceived level of importance of the revenue management tools by hoteliers in Turkey?

• RQ2.3: What is the impact of the revenue management tools on hotels’ sales?

16


RQ3: Channel management

• RQ3.1: What is the importance of the distribution channels used by hotels in Turkey?

• RQ3.2: Which types of contract do hotels in Turkey mostly use in their relationships with distributors?

RQ4: Revenue management team

• RQ4: Who is in charge of revenue management implementation in hotels in Turkey?

RQ5: Revenue management software

• RQ5: What are hotel managers’ perceptions about the specialised revenue management software?

17


RQ6: Revenue management process

• RQ6.1: How do hoteliers in Turkey measure the performance of their properties?

• RQ6.2: How do hoteliers in Turkey forecast the future sales, revenues, occupancy?

• RQ6.3: To what degree do hoteliers in Turkey consider customers’ characteristics and preferences when applying various revenue management tools?

• RQ6.4: How do hoteliers in Turkey react to competitor moves in prices?

18


RQ7: Factors, influencing the application of revenue management by hotels in Turkey

• RQ7.1: Does the size of the hotel influence the application of specific revenue management practices by its managers?

• RQ7.2: Does the category of the hotel influence the application of specific revenue management practices by its managers?

• RQ7.3: Does the location of the hotel influence the application of specific revenue management practices by its managers?

• RQ7.4: Does the affiliation to a hotel chains influence the application of specific revenue management practices by its managers?

19

MethodologyResearch approach and data collection

• Survey > online questionnaire

• The managers of 2080 properties were contacted (that is 66.43% of all 3131 licenced accommodation establishments in Turkey in 2014).

• Respondents were offered a complimentary e-book for completing the questionnaire.

• Two reminders sent 4 and 8 weeks after initial invitation.

• 105 completed questionnaires (5.05% response rate or 3.35% of all accommodation establishments in Turkey).

20

MethodologySample characteristics

21

Number of respondents Percent

Category 1 star 5 4.8

2 stars 14 13.3

3 stars 18 17.1

4 stars 16 15.2

5 stars 52 49.5

Size Up to 50 rooms 31 29.5

51-100 rooms 13 12.4

101-150 rooms 14 13.3

Over 150 rooms 47 44.8

Location Urban 61 58.1

Seaside 30 28.6

Mountain 9 8.6

Countryside 5 4.8

Chain affiliation Chain member 58 55.2

Independent 47 44.8

Total 105

MethodologyQuestionnaire

• Section 1: Characteristics of the accommodation establishment

• Section 2: Revenue centres

• Section 3: RM tools – frequency of application, importance, impact on revenues

• Section 4: RM team – RM responsibilities, intentions to hire

• Section 5: RM software – impact on RM

• Section 6: Channel management – channels, importance, contracts

• Section 7: RM metrics

• Section 8: Agreement with various statements

22

MethodologyData analysis

• Mann-Whitney U-test

• Kruskal-Wallis χ2 test

• Paired samples t-test

23

Discussion of resultsRevenue centres

24

0

20

40

60

80

100

120

• Application

Discussion of resultsRevenue centres

25

0

1

2

3

4

5

6

• Potential for development

Discussion of resultsPricing and non-pricing tools and sales techniques

• Application, importance and impact

26

0

0,5

1

1,5

2

2,5

3

3,5

Frequency of application Importance for the industry Impact on property sales

Discussion of resultsChannel management

• Channel importance

27

0

0,5

1

1,5

2

2,5

3

3,5

4

4,5

5

GDSs OTAs Tour operators Travel agents Group buyingwebsites

Direct sales via thewebsite

Other direct sales(email, phone)

Discussion of resultsChannel management

• Types of contracts: frequency of application

28

0

0,5

1

1,5

2

2,5

3

3,5

Commitment Allotment Free sale Upon-request

Discussion of resultsRM team

Revenue management responsibility

RM department Revenue

manager

Marketing

manager

Front office

manager

General

managers

Chain affiliation (Pearson χ2=30.795, df=4, p<0.01)

Independent hotels 0 5 5 14 23

Affiliated hotels 4 31 7 5 11

Category (Pearson χ2=54.787, df=16, p<0.01)

1 star 0 0 0 0 5

2 stars 0 0 0 5 9

3 stars 0 2 3 8 5

4 stars 1 5 5 2 3

5 stars 3 29 4 4 12

Location (Pearson χ2=24.285, df=12, p<0.05)

Urban 3 15 7 15 21

Seaside 1 13 5 3 8

Mountain 0 8 0 0 1

Rural 0 0 0 1 4

Size (Pearson χ2=78.510, df=12, p<0.01)

Up to 50 rooms 0 3 1 8 19

51-100 rooms 0 0 5 7 1

101-150 rooms 0 5 6 0 3

Over 150 rooms 4 28 0 4 11

Total 4 36 12 19 34

29

Discussion of resultsRM team

• Most of the respondents (48 out of 65 or 73.8%) that report not having a revenue manager or a department do not intend to hire a revenue manager, probably because of their small size and low category which make such position economically not viable.

30

Discussion of resultsRM software

Software Frequency

Opera 4

Delphi 4

Trust 3

Elektra 2

Rategain 2

Reseliva 2

Erbasoft 1

Hotelrunner 1

Ideas 1

Amadeus RMS 1

Other 6

31

• The respondents were not keen on using specialised revenue management software (m=2.59) and only 38 show willingness to pay for it.

Discussion of resultsRM process

• RM metrics: the most frequently used statistics include occupancy (104 respondents, or 99%), ADR (97, or 92.4%), and RevPAR (74, or 70.5%). GOPPAR is reported by only 20 (19%) of the managers.

• Forecasting: 74 of the respondents (70.47%) indicate that they use historical methods for forecasting their future sales, revenues and occupancy, while 31 (29.53%) mentioned statistical methods (regression analysis)

32

Discussion of resultsRM process

Mean

If occupancy is low it is best to lower the prices 4.43

Each customer is equally important for the hotel 4.03

We try to attract every potential customer 4.49

If competitor decrease prices we decrease our prices too 3.52

If competitor increase prices we increase our prices too 4.21

Customers prefer lower prices than higher quality 2.64

Maintaining good relations with the distributors is important for

property’s revenues

4.13

Selling additional services is important for property’s revenues 3.69

When we set the prices and booking terms we consider customers’

perception of these

3.71

In general the application of the RM tools contributes positively to the

revenues of our property

3.94

33

• Level of agreement with various statements

ConclusionSummary answers to research questions

34

Research question Answer

RQ1: Revenue centres in the

hotels

RQ1.1: Which are the revenue

centres of hotels in Turkey?

Main revenue centres rooms (73% of

revenues), restaurant, bar/lobby bar,

minibar

RQ1.2: Which revenue centres

have greatest potential for

development?

Rooms, restaurant, bar/lobby bar


35


RQ2: Revenue management tools

RQ2.1: What is the level of

application of the revenue

management tools by hoteliers

in Turkey?

Most applied tools are rooms

availability guarantee and price

discrimination; least applied are

overcontracting and overbooking

RQ2.2: What is the perceived

level of importance of the

revenue management tools by

hoteliers in Turkey?

Most important tools are rooms

availability guarantee and price

discrimination; least important are

overcontracting and overbooking

RQ2.3: What is the impact of

the revenue management tools

on hotels’ sales?

Most tools have similar perceived

impact on sales with slight advantage

of room availability guarantee


36


RQ3: Channel management

RQ3.1: What is the importance

of the distribution channels

used by hotels in Turkey?

OTAs is the single most important

distribution channel, followed by the

direct sales via the hotel’s website, the

travel agents and the tour operators

RQ3.2: Which types of contract

do hotels in Turkey mostly use

in their relationships with

distributors?

Commitment and allotment are most

frequently used contracts with the

distributors


37


RQ4: Revenue management team

RQ4: Who is in charge of

revenue management

implementation in hotels in

Turkey?

A separate revenue management

department or a revenue manager

position is reported by the chain

affiliated, 4- and 5-star, and very large

(over 150 rooms) hotels


38


RQ5: Revenue management

software

RQ5: What are hotel managers’

perceptions about the

specialised revenue

management software?

The managers of largest hotels (over

150 rooms), chain affiliated, seaside, 3-

, 4- and 5-star properties seem more

inclined to use specialised licenced

software


39


RQ6: Revenue management process

RQ6.1: How do hoteliers in Turkey

measure the performance of their

properties?

Occupancy, ADR, RevPAR


forecast the future sales, revenues,

occupancy?

Historical methods are more widely used than

statistical

RQ6.3: To what degree do hoteliers in

Turkey consider customers’

characteristics and preferences when

applying various revenue

management tools?

In general, customers’ characteristics and

preferences are taken into consideration


react to competitor moves in prices?

Increase prices if competitors increase their

prices; Hotels competing on price will decrease

the prices if competitors do so; hotels

competing on quality are less likely to do it.


40


RQ7: Factors, influencing the application of revenue management by

hotels in Turkey

RQ7.1: Does the size of the hotel

influence the application of

specific revenue management

practices by its managers?

Yes, larger hotels have better developed

revenue management practices than

smaller properties

RQ7.2: Does the category of the

hotel influence the application of



Yes, higher category hotels have better

developed revenue management

practices than lower category properties


41


RQ7: Factors, influencing the application of revenue management by

hotels in Turkey

RQ7.3: Does the location of the

hotel influence the application of



Yes, in general seaside and urban

properties have better developed revenue

management practices than mountain

and rural properties, although the

differences depend on the specific

practice.

RQ7.4: Does the affiliation to a

hotel chains influence the

application of specific revenue

management practices by its

managers?

Yes, chain affiliated hotels have much

better developed revenue management

practices than independent properties in

every aspect

ConclusionLimitations

• Sample size is only 105 respondents

• 5-star hotels overrepresented

• The aggregated results of this research cannot be generalised for the country as a whole, but the findings could give an indication about the differences of the application of the various revenue management practices by category, chain affiliation, location and size of the accommodation establishments

42

Conclusion

Future research• Larger samples

• Channel management

• Educational and training needs of hotel managers in the area of revenue management

• Link between revenue management practices of hotels in Turkey and the customers’ perceptions of their fairness

• Other empirical settings, especially focusing on countries in Central and Eastern Europe, Middle East, Latin America and Africa.

43

Manuscript references (1)

• Abrate, G., Fraquelli, G. & Viglia, G. (2012). Dynamic pricing strategies: Evidence from European hotels. International Journal of Hospitality Management, 31(1), 160-168.

• Anderson, C. K., and Xie, X. (2010). Improving hospitality industry sales: Twenty-five years of revenue management. Cornell Hospitality Quarterly, 51(1), 53-67.

• Aubke, F., Wöber, K., Scott, N., & Baggio, R. (2014). Knowledge sharing in revenue management teams: Antecedents and consequences of group cohesion. International Journal of Hospitality Management, 41, 149–157.

• Baggio, R., and Klobas, J. (2011), Quantitative methods in tourism. A handbook. Bristol: Channel View Publications.

• Beck, J., Knutson, B., Cha, J. & Kim, S. (2011). Developing revenue managers for the lodging industry. Journal of Human Resources in Hospitality & Tourism, 10(2), 182-194.

• Buckhiester, B. (2012). Optimizing total revenue management. Hotelnewsnow.com, 23rd May. Available online at: http://www.hotelnewsnow.com/Article/8251/Optimizing-total-revenue-management (Accessed on 05.01.2014).

• Carvell, S. A. and Quan, D. A. (2008). Exotic reservations – low price guarantee. International Journal of Hospitality Management, 27(2), 162-169.

• Chen, C. and Kachani, S. (2007). Forecasting and optimisation for hotel revenue management. Journal of Revenue and Pricing Management, 6(3), 163-174.

• Chen, C.-C. and Schwartz, Z. (2013). On revenue management and last minute booking dynamics. International Journal of Contemporary Hospitality Management, 25(1), 7-22.

• Choi, S. & Kimes, S. E. (2002). Electronic distribution channels’ effect on hotel revenue management. Cornell Hotel and Restaurant Administration Quarterly, 43(3), 23-31.

• Cleophas, C., and Frank, M. (2011). Ten myths of revenue management – a practitioner’s view. Journal of Revenue and Pricing Management, 10(1), 26-31.

• Croes, R. and Semrad, K. (2012). Discounting works in the hotel industry: a structural approach to understanding why. Tourism Economics, 18(4), 769-779.

• Cross, R., Higbie, J., and Cross, D. (2009). Revenue management’s renaissance: a rebirth of the art and science of profitable revenue generation. Cornell Hospitality Quarterly, 50(1), 56—81.

• Demirciftci, T., Cobanoglu, C., Beldona, S. and Cummings, P. (2010). Room rate parity analysis across different hotel distribution channels in the U.S. Journal of Hospitality Marketing and Management, 19(4), 295-308.

• El Gayar, N. F., Saleh, M., Atiya, A., El-Shishiny, H., Zakhary, A. A. Y. F. & Habib, H. A. A. M. (2011). An integrated framework for advanced hotel revenue management. International Journal of Contemporary Hospitality Management, 23(1), 84-98.

44

http://www.hotelnewsnow.com/Article/8251/Optimizing-total-revenue-management


• El Haddad, R. (2015). Exploration of revenue management practices – case of an upscale budget hotel chain. International Journal of Contemporary Hospitality Management, 27(8), 1791-1813.

• Emeksiz, M., Gursoy, D., & Icoz, O. (2006). A yield management model for five-star hotels: Computerized and non-computerized implementation. International Journal of Hospitality Management, 25(4), 536-551.

• Enz, C., Canina, L. & Lomanno, M. (2004). Why discounting does not work: The dynamics of rising occupancy and falling revenue among competitors. Cornell Hospitality Report, 4(7).

• Frechtling, D. C. (2001). Forecasting tourism demand: Methods and strategies. Oxford: Butterworth-Heinemann.

• Gehrels, S. and Blanar, O. (2012). How economic crisis affects revenue management: the case of Prague Hilton hotels. Research in Hospitality Management, 2(1-2), 9-15.

• Guadix, J., Cortes, P., Onieva, L. & Munuzuri, J. (2010). Technology revenue management system for customer groups in hotels. Journal of Business Research, 63(5), 519-527.

• Güler, M .E. (2012). Prioritization of revenue management factors: A synthetic extent analysis approach. Ege Academic Review, 12(2), 161-170.

• Hadjinicola, G. C. & Panayi, C. (1997). The overbooking problem in hotels with multiple tour-operators. International Journal of Operations & Production Management, 17(9), 874-885.

• Hayes, D. K. and Miller, A. A. (2011). Revenue management for the hospitality industry. Hoboken, N. J.: John Wiley and Sons.

• Haynes, N. and Egan, D. (2015). The future impact of change in rate parity agreements on hotel chains. Journal of Travel and Tourism Marketing, forthcoming, doi:10.1080/10548408.2015.1063897

• Heo, C. Y. (2013). Restaurant revenue management. In Legoherel, P., Poutier, E., & Fyall, A. (eds.). Revenue management for hospitality and tourism. Woodeaton, Oxford: Goodfellow Publishers ltd., pp. 118-129.

• Hwang, J., and Wen, L. (2009). The effect of perceived fairness toward hotel overbooking and compensation practices on customer loyalty. International Journal of Contemporary Hospitality Management, 21(6), 659—675.

• Illum, S. F., Ivanov, S. and Liang, Y. (2010). Using virtual communities in tourism research. Tourism Management 31(3), 335-340.

• Ingold, A., McMahon-Beattie, U. and Yeoman, I. (Eds.) (2001). Yield management. Strategies for the service industries. London: Continuum.

• Ivanov, S. (2006). Management of overbookings in the hotel industry – basic concepts and practical challenges. Tourism Today, 6, 19-32.

• Ivanov, S. (2007). Conceptualizing cannibalisation: the case of tourist companies. Yearbook of International University College, 3, 20-36.

• Ivanov, S. (2014). Hotel revenue management: from theory to practice. Varna: Zangador.

• Ivanov, S. (2015). Optimal overbooking limits for a hotel with three room types and with upgrade and downgrade constraints. Tourism Economics 21(1), 223-240.

45


• Ivanov, S., Stoilova, E., and Illum, S. F. (2015). Conflicts between accommodation establishments and travel agencies. Tourism and Hospitality Research15(1), 54-70.

• Ivanov, S., and Zhechev, V. (2012). Hotel revenue management – a critical literature review. Tourism, 60(2), 175-197.

• Kimes, S. E. (1989). Yield management: a tool for capacity-constrained service firms. Journal of Operations Management, 8(4), 348–363.

• Kimes, S. E. (2009). Hotel revenue management in an economic downturn: Results of an international study. Cornell Hospitality Report 9(12)

• Kimes, S. E. (2011). The future of hotel revenue management. Journal of Revenue and Pricing Management, 10(1), 62-72.

• Kimes, S. E. & Singh, S. (2009). Spa revenue management. Cornell Hospitality Quarterly, 50(1), 82-95.

• Kimes, S. E. & Thompson, G. M. (2004). Restaurant revenue management at Chevys: determining the best table mix. Decision Sciences, 35(3), 371-392.

• Kimes, S. E. & Wirtz, J. (2003). Has revenue management become acceptable? Findings from an international study on the perceived fairness of rate fences. Journal of Service Research, 6(2), 125-135.

• Koide, T. & Ishii, H. (2005). The hotel yield management with two types of room prices, overbooking and cancellations. International Journal of Production Economics, 93-94, 417-428.

• Kuyumcu, A. H. (2002). Gaming twist in hotel revenue management. Journal of Revenue and Pricing Management, 1(2), 161-167.

• Legoherel, P., Poutier, E., and Fyall, A. (Eds.) (2013). Revenue management for hospitality and tourism. Woodeaton, Oxford: Goodfellow Publishers ltd.

• Lim, C., Chang, C. & McAleer, M. (2009). Forecasting h(m)otel guest nights in New Zealand. International Journal of Hospitality Management, 28(2), 228-235.

• Maier, T. A. (2011). Hospitality industry revenue management performance modelling: Uncovering issues associated with inconsistencies in price parity across multiple distribution channels in the US hotel market. International Journal of Revenue Management, 5(4), 290-307.

• Maier, T. A. (2013). Revenue management implications of branded vs. independent hotels price-parity and online distribution effectiveness. International Journal of Revenue Management, 7(3-4), 223-243.

• Mauri, A. G. (2012). Hotel revenue management: Principles and practices. Milan-Torino: Pearson Italia.

• Ministry of Culture and Tourism (2015a). Statistics of tourism licenced facilities. Retrieved on 29th November 2015 from http://www.kultur.gov.tr/EN,36575/ministry-licenced-establishments.html

• Ministry of Culture and Tourism (2015b). Distribution of Number of Arrivals and Nights Spent by Country of Residence. Retrieved on 29th November 2015 from http://www.kultur.gov.tr/EN,47833/ministry-licenced-establishments.html

• Netessine, S. & Shumsky, R. (2002). Introduction to the theory and practice of yield management. INFORMS Transactions on Education, 3(1), 34-44.

• Ng, I. C. L. (2009). The pricing and revenue management of services: A strategic approach. London: Routledge.

46


• Okumus, F. (2004). Implementation of yield management practices in service organisations: empirical findings from a major hotel group. The Service Industries Journal, 24(6), 65-89.

• Orkin, E. (2003). The emerging role of function space optimisation in hotel revenue management. Journal of Revenue and Pricing Management, 2(2), 172-174.

• Queenan, C. C., Ferguson, M. E. & Stratman, J. K. (2011). Revenue management performance drivers: An exploratory analysis within the hotel industry. Journal of Revenue and Pricing Management, 10(2), 172-188.

• Pekgün, P., Menich, R. P., Acharya, S., Finch, P. G., Deschamps, F., Mallery, K., Van Sistine, J., Christianson, K. & Fuller, J. (2013). Carlson Rezidor hotel group maximizes revenue through improved demand management and price optimization. Interfaces, 43(1), 21-36.

• Rannou, B., and Melli, D. (2003). Measuring the impact of revenue management. Journal of Revenue & Pricing Management, 2(3), 261-270.

• Rasekh, L. & Li, Y. (2011). Golf course revenue management. Journal of Revenue and Pricing Management, 10(2), 105-111.

• Schwartz, Z. (2008). Time, price and advanced booking of hotel rooms. International Journal of Hospitality and Tourism Administration, 9(2), 128-146.

• Selmi, N. & Dornier, R. (2011). Yield management in the French hotel business: An assessment of the importance of the human factor. International Business Research, 4(2), 58-66.

• Shy, O. (2008). How to price. A guide to pricing techniques and yield management. Cambridge University Press.

• Talluri, K. T. and van Ryzin, G. (2005). The theory and practice of revenue management. New York: Springer Science+Business Media.

• Tranter, K. A., Stuart-Hill, T. and Parker, J. (2008). Introduction to revenue management for the hospitality industry. Harlow: Pearson Prentice Hall.

• Vinod, B. (2004). Unlocking the value of revenue management in the hotel industry. Journal of Revenue and Pricing Management, 3(2), 178-190.

• Vladimirov, Z. (2015). Factors for the e-business adoption by small tourism firms and the role of shadow economic practices. European Journal of Tourism Research, 10, 5-34.

• Wang, X.L., Heo, C.Y., Schwartz, Z., Legohérel, P., and Specklin, F. (2015). Revenue management: progress, challenges, and research prospects. Journal of Travel & Tourism Marketing, forthcoming, doi: 10.1080/10548408.2015.1063798

• Weatherford, L. R. & Kimes, S. E. (2003). A comparison of forecasting methods for hotel revenue management. International Journal of Forecasting, 19(3), 401-415.

• Yeoman, I. and McMahon-Beattie, U. (Eds.) (2011). Revenue Management. A Practical Pricing Perspective. Palgrave Macmillan.

• Yeoman, I. and McMahon-Beattie, U. (Eds.) (2004). Revenue Management and Pricing: Case Studies and Applications. Thomson Business Press.

• Zarraga-Oberty, C. & Bonache, J. (2007). Human factors in the design of revenue management systems in multinational corporations. International Journal of Revenue Management, 1(2), 141-153.

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