empirical findings in three,four and five stars hotels in the city of madrid

IMPLEMENTATION OF YIELD MANAGEMENT

Practices in hotel industry: Empirical Findings in three,

four and five stars hotels in the city of Madrid (Spain).

Master Thesis submitted at the

IMC University of Applied Sciences Krems

Master-Programme “Tourism and Leisure Management”

& Universidad Rey Juan Carlos

“Master in International Tourism Management”

by

Raúl MATEO LAPUENTE

for the award of the academic double degree

Master of Arts in Business (MA)

Thesis Coach: Alberto Romero Ania, Prof

Submitted on: 14.08.2010

Raúl Mateo Lapuente II

STATUTORY DECLARATION

“I declare in lieu of an oath that I have written this Master Thesis myself and that I

have not used any sources or resources other than stated for its preparation. I

further declare that I have clearly indicated all direct and indirect quotations. This

Master Thesis has not been submitted elsewhere for examination purposes.”

_______________________ _______________________________

Date Signature

Raúl Mateo Lapuente III

ACKNOWLEDGEMENTS

At the time of completing my Master Thesis, I would like to acknowledge a number

of people who have helped me throughout this research.

Special thanks are in order, to the Rector of IMC, FH Krems University of Applied

Sciences Prof. (FH) Mag. Eva Werner and to the Dean of the Faculty of Tourism of

Universidad Rey Juan Carlos of Madrid Catalina Vacas Ph.D. for giving me the

opportunity to study at IMC, FH Krems University of Applied Sciences in Austria. I

would also like to thank IMC Deputy Head of International Relations Prof. (FH) Dr.

Maximilian Schachner for his precious time, enthusiastic support and invaluable

advice given during my stay. Next, I would like to express great thanks to my

supervisor; Prof. Alberto Romero Ania, without his help, commitment and

guidance, this research would never have been completed. My acknowledgement

to Prof. Pilar Talón Ballesteros, her technical advice was essential for the

completion of this Master Thesis. Thanks to all of them for arising my interest in

this field.

My sincere thanks to my family, for always being there giving me all kinds of

support and energy, through years of studies which have being the foundations of

this work.

Finally, I owe many thanks to my great friends, Tess León whom I admire both

professionally as humanly, Pablo Rodriguez and José Luis Cañadas for their kind

generosity in sharing and enriching me professionally, and Karin Krainer for her

love and respect always present; they have always been there supporting and

encouraging me, particularly at stressful times. Their support has inspired me to

work hard and believe in my capabilities as well in this research.

My most sincere gratitude to all of them.

Raúl Mateo Lapuente IV

ABSTRACT

With this work we expect to know the concept in depth and contribute to the

assessment of the degree of implementation of Yield Management strategies as

an effective technique for decision making and profitability in three, four and five-

star hotels of the city of Madrid (Spain), with the new competitive environment and

growth of new technologies, there is a need to innovate in price management and

demand capacity to maximize profits.

By studying a thorough review of literature, the most representative variables of

the model were determined to measure yield management in the hotels subject to

be reviewed. Revenue Managers were sent a self-administered questionnaire

about the actions that are considered integrate the process. This paper presents a

multivariate analysis of the impact caused by YM practices in Madrid’s hotels

together with the profits and obstacles of deploying the tool. It attempts to

establish the differences existing between hotel categories based on whether they

are chain owned hotels or independently owned and the existing degree of

implementation of YM culture.

The study shows that three, four and five star hotels in Madrid are characterized

for belonging to hotel chains showing a small number of independent hotels, this is

a determining factor when looking at the YM implementation degree. Chain owned

hotels have a higher degree of these practices than those independent which

present a medium degree of implementation. Madrid hoteliers think that a good

practice of this management strategy is beneficial to maximize benefits and helps

foresee hotel management and environmental imbalances.

Raúl Mateo Lapuente V

TABLE OF CONTENTS

Statutory declaration................................................................................................ II

Acknowledgements ................................................................................................ III

Abstract ..................................................................................................................IV

Table of contents .....................................................................................................V

List of tables and figures.......................................................................................VIII

Abbreviations..........................................................................................................IX

CHAPTER 1 Introduction......................................................................................... 1

1.1. Background to the study............................................................................. 1

1.2. Research methodology .............................................................................. 2

1.3. Outline of Master Thesis ............................................................................ 3

CHAPTER 2 Origins and definitions of Yield Management..................................... 4

2.1. Yield Management’s History in United States ............................................ 9

2.2. Development of Yield Management in Spain ........................................... 11

2.3. Yield Management main strategies .......................................................... 13

2.3.1. Jones and Hamilton’s Implementation Model .................................... 14

2.3.2. Donaghy and McMahon’s Implementation Model.............................. 16

2.3.3. Jones and Kewin’s Implementation Model ........................................ 18

2.3.4. Yeoman and Watson’s Implementation Model .................................. 20

2.3.5. Emeksiz’s Implementation Model ..................................................... 22

2.3.6. Figueroa, Talón and Vacas’s Implementation Model......................... 24

2.4. Case study: Yield Management Implementation in the Community of

Madrid ................................................................................................................ 29

CHAPTER 3 Research methodology .................................................................... 33

3.1. Approach to the study .............................................................................. 33

Raúl Mateo Lapuente VI

3.1.1. Hypothesis ......................................................................................... 33

3.1.2. Research Question ............................................................................ 34

3.2. Proposed Methodological Approach ........................................................ 34

3.2.1. Secondary sources ............................................................................ 36

3.2.2. Primary sources................................................................................. 39

3.3. Quantitative research process.................................................................. 39

3.3.1. Questionnaire design......................................................................... 39

3.3.2. Questionnaire Analysis ...................................................................... 40

3.4. Sampling and sample size ....................................................................... 44

3.4.1. Design of the sample frame............................................................... 45

3.4.2. Sample size and error level ............................................................... 45

3.4.3. Effective final sample......................................................................... 46

3.4.4 Bias and error level............................................................................. 47

3.5. Fieldwork: Protocols and results .............................................................. 48

3.5.1. Pre-test questionnaire........................................................................ 49

3.5.2. Fieldwork protocols............................................................................ 49

3.5.3. Issues occurred during the fieldwork ................................................. 51

CHAPTER 4 Findings and analysis....................................................................... 53

4.1. Descriptive data of effective sample......................................................... 53

4.1.1. Socio-demographic analysis.............................................................. 53

4.1.2. Descriptive analysis of Yield Management variables......................... 60

4.2. Yield Managment implementation multivariable analysis......................... 67

CHAPTER 5 Conclusions and recommendations ................................................. 73

5.1. Conclusions.............................................................................................. 73

5.2. Limitations ................................................................................................ 75

5.3. Recommendations for further research.................................................... 76

Raúl Mateo Lapuente VII

Bibliography........................................................................................................... 77

Appendix................................................................................................................ 84

Raúl Mateo Lapuente VIII

LIST OF TABLES AND FIGURES

Table 1: Structure of Master Thesis 3

Table 2: Contributions of the authors to the concept 4

Table 3: Model implementation by Jones and Hamilton 14

Table 4: Model implementation by Donaghy and McMahon 16

Table 5: Model implementation by Jones and Kewin 19

Table 6: Model implementation by Yeoman and Watson 21

Table 7: Model implementation by Emeksiz 23

Table 8: Model implementation by Figueroa, Talón and Vacas 24

Table 9: YM philosophy implementation model 36

Table 10: Population distribution by category 46

Table 11: Response rate 47

Table 12: Bias and error level 47

Table 13: Weighting factor 48

Table 14: Hotel size 55

Table 15: Applies Yield Management 56

Table 16: Implementation date of Yield Management 57

Table 17: Hotel management model 58

Table 18: Hotel web on-line bookings 65

Figure 1: Hotel category 54

Figure 2: Hotel independence 59

Figure 3: Person responsible for Yield Management 60

Figure 4: Yield Management software 61

Figure 5: Demand forecasting Revenue Management department 64

Figure 6: Motivate staff by Upselling and Crosselling 67

Figure 7: Increase profits 68

Raúl Mateo Lapuente IX

ABBREVIATIONS

ARI Average Rate Index

CRS Computerized Reservation Systems

CPA Customer-Profitability-Analysis

DYNAMO Dynamic Inventory Allocation and Maintenance Optimization

System

GDS Global Distribution Systems

IRG Revenue Generation Index

ICT Information, communications and technology

MPI Market Penetration Index

MSPA Market-Segment-Profitability-Analysis

PMS Property management system

RM Revenue Management

YM Yield Management

Chapter 1: Introduction

Raúl Mateo Lapuente 1

CHAPTER 1

INTRODUCTION

1.1. Background to the study

Since the eighties the service sector, airlines and hotels in the United States are

affected by increased competition, this is where YM becomes an important tool for

increasing productivity and profitability in an increasingly competitive market. This

is thanks to the possibilities that computer systems offer and will offer in the future

and because YM systems are becoming increasingly accessible (Karadjov and

Farahmand, 2007).

Computerized control systems and Revenue management are clearly increasing,

where American carriers invested in its technological development, in what are

known as GDS and CRS. The computerization of YM systems in tourism is grow-

ing in recent years, and their use in tourism businesses, such as car rentals,

cruises, trains, planes and hotels. However the hotel industry seems to be at a

slower pace than other sectors as aviation or maritime and tools used today have

a very high proportion of non-automatic.

The vast majority of tourism businesses have products or services with a common

denominator, fixed-capacity products which are perishable or non-storable in time,

also the market is composed of clients who are willing to consume different pro-

ducts at different prices, so it is possible to segment the demand for the use of the

services, being able to create different market segments. Companies living in an

information & technology environment find the need of searching for new ways of

controlling prices with a key tool in business management.

In a hotel context, YM is a sophisticated approach to managing room sales based

on a detailed analysis and close monitoring of demand (Jones, 1999).



A review of literature shows that there is no commonly agreed definition of YM,

there is a lack of conceptual clarity about YM key features, and no systems

analysis of YM. There is also some stronger evidence emerging that yield

management is not fully understood in industry.

1.2. Research methodology

In undertaking any research and selecting the methodology, researchers have to

be aware of the nature of the situation being studied or the question being asked,

as well as any possible limitations to the research, such as time, resources and

availability of information. It is of a vital importance as well for the research topic to

match the methodology (Jennings, 2001). Selecting the appropriate research

method is very important when doing project research, in order to achieve its aims

and objectives. The methodology utilized in this research has basically being

based on conducting a wide-range review of secondary data and then a self-

administered questionnaire in order to obtain primary data.

Chapter three presents the detailed methodology that was adopted in this

research. Secondary data was collected from books, articles, journals and studies

and was encompassed in the literature review. As for primary data, the researcher

has conducted 160 questionnaires (theorical sample), directed to Revenue

Managers or hotel managers of three, four and five star hotels of the city of

Madrid. Subsequently the main findings and analysis will be presented in chapter

four.



1.3. Outline of Master Thesis

The following table presents the overall structure of the Master Thesis.

Table 1. Structure of Master Thesis

Source: Own elaboration

Chapter 1. Introduction to the research study. It discusses the background of

the study and introduces the aim and objectives, then briefly discusses

research methodology of the Master Thesis.

_____________________________________________________________

Chapter 2 provides a review of relevant literature with aims and objectives, the

following issues are discussed, United States Yield Management history,

Introduction to Spain’s Yield Management Development, Yield Management’s

Main Strategies

_____________________________________________________________

Chapter 3 presents the research methodology and explains the methodological

approaches that have been used in order to collect the most relevant

information. It also mentions the criteria followed in conducting the quantitative

research.

_____________________________________________________________

Chapter 4. Classification and analysis of the main findings of data collected

through primary research will be presented in this chapter.

_____________________________________________________________

Chapter 5 presents conclusions of the study of this Master Thesis, and it

suggests recommendations for future research.

Chapter 2: Origins and Definitions of Yield Management


CHAPTER 2

ORIGINS AND DEFINITIONS OF YIELD MANAGEMENT

When it comes to defining YM or Revenue Management (from now on RM) we

find there is no clear difference between both concepts for the authors use both

terms indistinctly. If we regard the Spanish translation, the correct term would be

YM when referring to profits and RM when referring to incomes (Figueroa, Talón

and Vacas, 2008). From Chávez and Ruiz’s study carried out in hotels in Sevilla,

the term YM is better known, although RM is experiencing a higher growth in its

use.

In Hotel trade the common name for the person responsible for the team that

coordinates tasks of YM o RM is the Revenue Manager. On the other hand, to be

able to establish a definition for the YM concept, I will mention that it arises as a

business practise regarding price management which consists in selling the right

room, to the right guest at the right price (Smith et al.1992) where the main

objective is to maximize profit for both the seller and the buyer (Kimes 1989).

Table two shows the contribution of the authors to the concept of YM and its

evolution until our days.

Table 2. Contributions of the authors to the concept

AUTHOR AND

YEAR

FIELD DEFINITION

Kimes et al. (1989)

Cruise

lines

Yield Management is the application of

information Systems and pricing strategies to

allocate the right capacity to the right customer

at the right place at the right time.

Smith et al.

(1992)

Air

transport

Revenue Management is a business practice

which sells the product, to the right customer, at



the right time, at the right price.

Liberman. (1993)

Hotel

industry

Yield Management is the practice of maximizing

profits on sales of perishable assets, such as

hotel rooms, through price controls, inventory

and improving service.

Jauncey,

Mitchell and Slamet. (1995)

Hotel

industry

Yield Management is an integrated, continuous

and systematic approach to maximizing room

revenue through the manipulation of room rates

in response to forecasted patterns of demand

Donahy et al.

(1997)

Hotel

industry

Yield Management is a technique for maximizing

income, aimed at increasing the net return

through the forecasting room availability in

certain market segments and an optimal price.

Lee-Ross and

Johns. (1997)

Hotel

industry

Yield Management is a procedure that tends to

maximize profits using information on the buying

and selling behaviors and setting price controls

and inventory.

Jones. (2000) Hotel

industry

Yield Management is a system for Hotels that

tries to maximize the benefit through serious

management and identifying the benefit of

market segments, assigning it value, establishing

rate structures, creating discounts and rules for

implementing advanced reservation process and

to monitor the effectiveness of these rules and

their implementation.

Hill. (2002) Hotel

industry

Yield Management is an approach to maximize

profit, given the costs related to the capacity that

are relatively fixed.

Gallego and Philips. (2005)

Hotel

industry

A flexible product as a “menu” of two or more

alternative, typically substitute, products offered

by a constrained supplier using a sales or



booking process. In this context, products

include not only physical products but also

service offerings.

Marchiona.

(2005)

Hotel

industry

Revenue Management is a methodology which

allows maximum revenue generation for future

service provision in a context in which

transactions have the following conditions: using

capital intensively, strong influence of fixed costs

in the cost structure, perishable nature of the

product or service, customers who make the

purchase decision with very different planning

horizons, customers making purchasing

decisions with elements of different rating.

Lai and Ng.

(2005)

Hotel

industry

Yield Management is used to contribute

optimally to inventory, develop strategies, so as

to fix prices for perishable inventory in order to

maximize revenue in a program.

Berman. (2005) Hotel

industry

Revenue management is an effective

mechanism to allocate a service provider's

relatively fixed capacity and to provide discounts

on a much broader scale.

Campa (2007) Hotel

industry

Yield Management is profit maximization through

efficient Management of perishable asset

through the determination of price and inventory

control.

Figueroa, Talón

and Vacas. (2008)

Hotel

industry

Yield Management is a management philosophy

that primarily helps companies with fixed

capacity, in the decision making process

(strategic and operational) on prices and

inventory. This philosophy is based on the

analysis of information, supported by science,



technology and common sense, contributing with

deep knowledge of market and product, thus

facilitating a correct forecast of demand and

adequate segmentation rates. Thus effectively

taking into account the time factor through

controlled reservations, the company can

maximize profits while satisfying customer

needs.

Source: Own elaboration.

For a better understanding of YM, we can say it is a model or strategy adopted by

companies that have in common: a fix capacity in the inventory of their product.

The product is perishable, which means it cannot be stored, therefore the

production and consumption of the product is simultaneous. It has high fix costs

(rent, staff, etc.) and low variable cost (hotel lighting, water supply consumed by

guests). The chance of market segmentation (high degree of segmentation in a

hotel will in return assure higher incomes). It is characteristic for having a variable

demand (seasonality directly affects the flow of demand) which will make the

company make decisions on the price: higher demand higher prices, in low

demand period they will try to have a higher volume of sales. Selling the product

in advance helps the company assure the sold units.

With all the characteristics previously named the application of YM within

organizations is to obtain the maximum profitability and to discuss how to maintain

that sustainability in time, this analysis searches how to maximize profits in the

hotel industry.

After checking bibliography it states that the YM process is part of the companies’

philosophy or culture, in my opinion, this philosophy is previous to the YM

process, where the company transmits the knowledge and information to the

customer and to the companies’ human resources as a decisive element to

achieve success in the application of this philosophy.



YM process is a management model that is applied after a companies’ philosophy

or culture as it will be seen ahead, all management models are set up of different

actions which are called strategies, which are defined as a behavioural pattern of

human actions, this is, it infers consistency when acting and are labelled as

strategies (Mintzberg, Henry et, al 1997). Behind a pattern there will be an

intended plan, where strategy can be given in two ways: intentional strategy and

elaborated strategy, within the elaborated strategy we can distinguish between

deliberated strategy where the intentions that existed were consciously assumed

as from the emerging strategy, which in absence of intentionality or because of it

(unconscious), patterns were developed.

Therefore, this behaviour leads us to a management model. Rumelt (1979) says,

“One person strategies are the tactics of another, what is strategic depends on

where one sits”. The hotel industry has adopted a management model similar to

those of the transport industry.

In summary the strategy is to create profitable economic situations and discern

how to sustain them over time, it also implies that a pattern may emerge and be

recognized in such a way that results in a formal plan.

After reviewing the definitions provided by the authors cited in table two, I will

contribute with a definition of YM, in the area of the hotel industry, defining it as a

strategy adopted or management model that primarily helps companies with fixed

capacity in the process of making strategic and operational decisions relating to

price and inventory. This model is based on the analysis of information, supported

by science, technology, which provides a deep understanding of market and

product. In turn, provides a proper estimate of demand and an adequate

segmentation of prices.

In this way, through effective monitoring of reserves and taking into account the

time factor (time and duration), where the company aims to reach a high income



and the maximum benefit (gross margin or Gross Profit) long-term in the same

way that meets the needs of the customer before purchase and during

consumption of the product or service.

2.1. Yield Management’s History in United States

The increasing competitiveness in the tourism sector, caused in most cases by

oversupply, has given great importance to the proper management of prices in

order to maintain profitability in companies. This continuous search to achieve

profit maximization, has led the industry to adopt Yield Management as contained

current and future management of most activities and tourist businesses.

The development of YM arises in connection with American Airlines airline

deregulation in 1978 and of a series of its own technological advances of the time.

Therefore, the introduction of YM is generally credited to American Airlines, in the

late seventies (Cross, 1997), having begun, the company, a former investigation

on managing inventory capacity and developing income optimization models.

The deregulation meant the removal of restrictions on domestic routes and prices;

this was the start point for low cost companies to arise in the market. These

companies were directed to price sensitive customers and to other social groups

that for economic reasons were using other means of transportation as the

automobile. It thus creates a highly competitive environment where traditional

companies lose price-sensitive customers who normally travelled on vacation.

However, this does not apply to business customers, who preferred the

advantages offered by the major airlines (schedules, destinations, greater

flexibility) and that low cost companies had deleted in order to establish lower

prices.

American Airlines decides to face this competitive environment by introducing a

program of discounted fares (American Super-Saver Fare), which provided a

surplus of seats at prices even lower than low cost carriers and keeping higher

rates in the remaining seats. They had to ensure that; first, business customers



would not buy discounted rates and, secondly, identify the surplus of seats for

customers. For this purpose constrained selling restrictions were designed, such

as: discounts for purchasing thirty days prior to departure, non-refundable, and

seven days minimum stay.

They achieved good results but, by not taking into account the different patterns of

demand and allocating the same number of seats at a discount price to all flights,

caused an excess of discounts on some occasions where they could have sold at

higher rates and in others a deficit when demand was low. American Airlines then

implemented a more complex system and created DYNAMO constituting the first

YM system in the industry. This system could better control and manage capacity

rates (Talluri and Van Ryzin, 2005).

DYNAMO was implemented in January 1985 along with a new fee schedule called

"Ultimate Super Saver Fares" which offered discounts based on a number of

restrictions as to buy two weeks in advance and having a Saturday overnight at

destination (Phillips, 2005).

The aim was to balance demand with supply and American Airlines was getting

through at low rates to stimulate demand in controlled flights of low occupancy,

while there was a limited supply of these tickets on high demand flights. This new

system achieved to produce competitive pressure and even the bankruptcy of

People's Express in 1985. Some of the problems of these companies were due to

the impossibility of implementing a dynamic pricing policy because they did not

have technologies such as CRS or GDS that major airlines did have, which made

YM application difficult (Anon, 1992; Cross, 1997).

There was a study on American Airlines, it follows that the key facts that led to the

birth of the YM model was the competitive environment caused by deregulation

and having the necessary technology, such as CRS, which facilitated the

automatic variation of prices. Additionally, there are various opinions about the real

innovation of YM, as some authors believe that it is not entirely a new technique,



previously rates were already set according to demand fluctuations (Boyce, 1991)

and the target was to obtain the maximum benefit in the long term (Lieberman,

1993). YM has been developed and refined over time and experience, as Relihan

(1989) What has changed is the frequency and scope of decision-making

procedure, Talluri and Van Ryzin (2005) prefer the innovation of the "method" in

making decisions, Jones and Hamilton (1992) and Lieberman (1993) agree on

quality improvement and information management with the help of technological

development.

On the other hand, the deregulation of air transport did not appear spontaneously

but as the result of litigation, the European community deregulation raised

gradually by the so called packages of measures implemented between 1987 and

1997, last year granted rights to fly and business establishment of any State

Member of the Community.

The liberalization of the sector in Europe accounted for two consequences: on one

hand, traditional companies (KLM, Iberia, British Airways, Air France, etc.)

reached an agreement not to compete with each other and on the other hand, "low

cost” companies like (Ryanair, Easyjet, etc.) appeared, what led to changes in the

structure and management of major airlines, the introduction of YM was not until

the late eighties with the full liberalization of air traffic.

2.2. Development of Yield Management in Spain

Moving forward in time we observe that YM began to be adopted by the American

hotel industry in the late eighties (Kimes, 1989), being the pioneer Marriott, which

was followed by large hotel chains like Quality Inn, Hyatt and Radisson (McMahon,

2000). It should nevertheless be noted that, even before the airlines, hotels used

pricing strategies based on season and inventory capacity constraints (Choi and

Cho, 2000).



The implementation of YM in Spain occurred one decade later, in the nineties,

when international hotel chains settled in major urban centres, Madrid and

Barcelona, introducing the YM concept in the management of their companies.

However, it was not until the late nineties when YM was implemented in the

Spanish hotel industry, first at major hotel chains and increasingly in independent

hotels and smaller companies. Spain, despite having the second largest number of

visitors from around the world and the third in terms of hotel supply concerns (after

USA and Japan), is anchored in a traditional management of their hotels. Hotels in

Madrid, "average YM activities begin in 2003. The emerging post of Revenue

Manager and weekly meetings did not appear until 2004. However, most of the

hotels introduced YM and software philosophy in 2005. There are cases where

this philosophy and its accompanying activities had seen the light in 1985, while

software implementation was not given until year 2000" (Figueroa et al., 2008).

With practice of the method and through technological development, which has

encouraged the implementation and improved information gathering according to

Jones and Hamilton (1992) and Liberman (1993) YM success does not depend

entirely on sophisticated technology but also the quality and the management of

information, as mentioned above, developing and facilitating the proper estimation

of demand and appropriate segmentation of the rates for each time (time factor). It

is also considered that for YM to be effective it is necessary for both managers

and employees to be aware of the information and analysis concerning the

decision making process of this practice, so it was deemed necessary the

implementation of a management model that meets the needs required for YM.

According to evidence presented YM model is applicable to service companies

that comply with the following characteristics: fixed capacity, perishable inventory,

high fixed costs, low variable costs, ability to segment the market, variable

demand and where sales can be made in advance. Those organizations applying

differentiation strategies that can provide price and length of service are even

more suitable for the application of YM.



Thus, in resort hotels it is more difficult to enforce than in urban YM for prices are

negotiated in advance with tour operators who usually have fixed prices. Although

having the presence of Internet, through indirect (OTA, Online Travel Agency), and

direct channels (hotel’s website) allow price changes at any time, which implies

certain independence from resort hotels regarding tour operators, since the old

closed prices negotiated become more open and in some cases implement Best

Rate Guaranteed (BAR, Best Available Rate).

On the other hand the implementation of YM is closely related to the size of the

hotel, the greater the size of the hotel industry, the greater its implementation, if

they are chain owned hotels the presence of YM is greater than in independent

hotels, having a larger area of operation this implementation is greater in

international chains. For all the above it follows that the complexity of the hotel will

determine the need to apply YM techniques in order to make it profitable and

maximize the benefits.

For a better understanding of research and data to express the current situation,

we must analyze the studies and projects related to the YM in the service industry

that have been developed recently. Most of the available literature does not

address the practices to be done for successful implementation, but focus more on

technical or implementation issues. Figueroa, Talón and Vacas (2008) highlight

the need to conduct a study covering this issue.

2.3. Yield Management main strategies

Different implementations of YM models found in the study literature which are to

be highlighted are the following: the Jones and Hamilton (1992), Donaghy y

McMahon (1995), Jones y Kewin (1997), Yeoman and Watson (1997), Emeksiz et

al (2006) and Figueroa, Talón and Vacas (2008).



2.3.1. Jones and Hamilton’s Implementation Model

Jones and Hamilton’s model (1992), was the first implementation model includes

seven phases: (1) Development of a YM culture (2) Analysis of demand, (3)

Determination of Price, (4) Market Segmentation, (5) Demand Behaviour Analysis,

(6) Monitoring of cancellations and refusals, (7) Evaluation (see table three).

Table 3. Implementation model by Jones and Hamilton

1. Developing a YM culture. • Designate a responsible person.

• Develope a YM strategy.

• Establish a forecast team.

• Start using the available data.

• Train front desk staff.

2. Demand Analysis. • Review the environmental factors.

• Identify competitors and local market characteristics.

• Identify the determinants of demand.

• Identify the hotel’s strengths and weaknesses.

• Predict levels of demand.

• Define objectives and strategies.

• Assign responsibilities by developing descriptions of the new jobs and

programming it.

• Monitor the competition.

3. Pricing (price-value). • Identify the market niche.

4. Market segmentation. • Determine segments.

• Establish an inventory of services available for each of the segments.



5. Behaviour of demand analysis.

• Evaluate changes in demand over time.

• Review the allocation of rooms to different segments as they are making

reservations.

• If the demand is high.

• Restrict availability. • Require a minimum stay.

• Only accept groups willing to pay high fares. • If demand is low.

• Identify price-sensitive segments. • Develop promotion packges.

• Establish promotions.

6. Monitoring of cancellations and refusals (declines and denials).

• Collect information on requests for reservation. • Analyze the behaviour of the demand and availability of reservations.

7. Evaluation.

• Daily review.

• Analyze prices.

• Provide tactical responses.

• Provide information to front desk staff.

8. Possible actions.

• Establish incentive and reward programs for staff.

Source: Adapted from Jones and Hamilton (1992)

This model highlights the importance of human resources in the implementation

process and stresses as limiting the null YM culture consciousness existing in

hotels. On one hand, the staff does not have deep knowledge on what the

philosophy implies and on the other hand it gives more importance to technology

than to people. According to Jones and Hamilton (1992) informal aspects of the

organization are more important than formal aspects and it is necessary to support

the use of YM to promote awareness and understanding of this culture among

staff and reward those who are involved with this practice. Another important



aspect is the identification of local competitors and their competitive advantages

and monitors them. In terms of segmentation this author points out the importance

of identifying the most profitable segments for the hotel and the behavioural

patterns of customers. Another important aspect is the analysis of variations in

demand and finally highlights the monitoring of cancellations and refusals to meet

actual demand, "unconstrained".

According to Jones and Hamilton (1992, pp.95) "the success of the YM systems

depend on both people and sophisticated technology. All hotel employees have

something to offer. The participation in this process needs to be acknowledged

and rewarded, in some cases with an appropriate incentive scheme. The quality of

the forecast information and the results will increase, as more people are involved

in the process. The latter is difficult because YM is complex and mainly depends

on ICT's".

2.3.2. Donaghy and McMahon’s Implementation Model

Donaghy and McMahon (1995), proposed a structured model in ten stages: (1)

Staff, (2) Analysis of demand, (3) Market Segmentation, (4) Determination of the

optimal combination of clients, (5) Analysis of displacement, (6) Establishment of

ability levels, (7) Introduction of YM system, (8) Client Reorientation (9) operational

evaluation, (10) Action (see table four).

Table 4. Implementation model by Donaghy and McMahon

1. Staff.

• To understand the concept among employees. • Emphasize the client/hotel interface.

• Appoint a foresight team.

• Provide data on: customers and markets.



2. Analysis of demand.

• Identify competitors and sources of demand.

• Identify t strengths and weaknesses.

• Predict the level of demand and booking patterns.

• Constantly monitor external factors.

3. Market segmentation.

• Identify the market.

• Segment the market (demographic, psychographic and geographically).

4. Determination of the optimal combination of client.

• Based on the predisposition to expenditure and volume of use.

5. Analysis of displacement. • Calculate the displacement.

• Avoid displacement of the most profitable businesses.

6. Setting capacity levels.

• Establish the capacity for each of segments.

7. Introduction of YM System.

• Hotel chains need tailor made systems.

• Small hotels use self-adapted versions of the systems to achieve greater

benefits.

8. Client Reorientation.

• Match business objectives with customer needs.

9. Operational Assessment. • Review layout of the rooms.

• Evaluate changes in demand.

• Identify additional factors that will drive demand.

10. Action.

• Fast implementation of the changes required.

Source: Adapted from Donaghy y McMahon (1995)



The most notable feature of the model is the importance of analysis of segments

and their behavioural patterns to forecast the daily demand, as Donaghy and

McMahon (1995) the effectiveness of YM is related to the proper market

segmentation, and this objective can only be achieved by linking the activities of

YM to the role of marketing. The authors give a classification of segments such as:

business, leisure, by geography, by length of stay, expenditure profile for income

and costs they generate. Donaghy and McMahon (2000) argue that the process

can be performed manually without the need to implement software to process

information. Typically hotels fail to implement YM computer systems during the

first two years, they can use core technology such as excel sheets, and PMS

database to obtain the necessary information.

2.3.3. Jones and Kewin’s Implementation Model

Jones and Kewin (1997), the proposed model conceptualizes the YM as a system

to maximize benefits and is based on six-sub interrelation between them. The

model incorporates several elements of previous models, the phases identified by

Donaghy et al. (1997) and the seven elements of Jones and Hamilton YM (1992)

(see table five).



Table 5. Implementation model by Jones and Kewin

Source: Adapted from YM hotel system by Kewin in Jones (2000)

This model distinguishes two subsystems, the strategic decision-making regarding

the decision-making long-term market segmentation and demand. Moreover, the

operational decision-making that focuses on the responses to requests from

customers. These decisions have a direct effect on the price at which they must

offer hotel rooms.



2.3.4. Yeoman and Watson’s Implementation Model

Yeoman and Watson (1997) define a model system where human activity acts to

the implementation of YM in the organization. YM is based on three interactive

subsystems: individual, forecasts and strategy shown below in table six.

The forecast subsystem is a continuous process because information is constantly

coming in and out of it. To make a good forecast implementation capacity is

essential, factors like the demand for tourism in the area, weather characteristics,

local competition, historical models of reservations, etc. Influence the ability to

predict performance in the company.

People subsystem, the process is basically developed by people and is where the

organization must designate a team responsible for developing and managing the

process.

Strategy subsystem should be supported by policies that determine the direction

for profit and its conservation. None of the subsystems can be developed in

isolation and must be taken together to produce an YM process.



Table 6. Implementation model by Yeoman and Watson

Source: Yeoman and Watson. (1997)

People

Yield Management

Team members

Meetings

Organitational

commitments

Strategy Benefits

Demand

Conservation

Monitoring

Historical

data

Knowledge of

Continuous process

Factors

Time

Stationality

Competitors

Riesgo

Information

Management

Forecast



2.3.5. Emeksiz’s Implementation Model

Emeksiz et al. (2006) proposed a model based on the first three previous models

trying to overcome some limitations such as size of hotel, its technological level

and the projection of the short and long term. The proposed model does not

require any YM software as mentioned, Emeksiz et al. The proposed model is

divided into five phases (see table seven).

The first two phases, Preparation and Analysis of Supply and Demand lay the

foundation for a successful YM implementation. The third phases are given

operational activities to the making of decisions that have to be made at dates

close to the arrival of the client. The fourth phase is responsible for evaluating the

process and finally the fifth stage monitors YM decisions taken, based on the

results of the fourth phase.



Table 7. Implementation model by Emeksiz

Source: Emeksiz et al. (2006)

I: Preparación a. Support and management

approval. b. YM Strategy Proposal. c. YM team up. d. Use of Database. e. Staff Training.

III: YM Implementation

Strategies a. Forecast market segments

demand levels b. Observation of Local De-

mand, Competition and Ex-ternal Factors.

c. Rate and capacity re-organization.

d. YM Operational Management on a daily basis.

IV: YM Assessment Activities a. Traditional Signs of income

and Occupancy. b. Quantitative YM Assessment.

Qualitative YM Assessment. c. Getting feedback of YM Op-

erations Staff. d. Support and recognition to

YM staff

II: Supply and Demand

Analysis

Analysis of Supply a. SWOT analysis: Identifica-

tion of Strengths and Weaknesses, Opportunities and Threats.

b. Analysis on Competition.

Analysis of Demand a. Description of the Sources

of Demand and Booking Patterns

b. Market Segmentation, de-termination and election of Market Segments

c. Organise Capacity and Dis-tribution Services by Market Segments

d. Determination of the condi-tions and restrictions apply-ing rate discounts

V: Monitoring and Review of

YM strategies



2.3.6. Figueroa, Talón and Vacas’s Implementation Model

All of the previous have been the basis for a new deployment model created by

Figueroa, Talón and Vacas (2008). The new model proposed by these authors are

structured in eight phases, lighter than previous models, in terms of stages and

contents, highlighting the main strategies and operations carried out in the process

and building on the concept. The phases are on two levels: the first five are at a

strategic level (long term), while the rest are in an operational or tactical (short-

term planning). See table eight.

Table 8. Implementation model by Figueroa, Talon and Vacas

STRATEGY LEVEL

1. Developing a culture of YM.

• Management and ownership Support.

• Establish and communicate YM strategies and goals.

• Match business goals with those of YM.

• Train staff mainly front-desk, reservations and sales.

• Report and make concepts understandable to the whole staff.

• Appoint a YM team.

• Appoint a team coordinator.

• Assign responsibilities.

• Use database.

• Inform customers about rate conditions.

• Match business goals with customer needs.

• Determine information necessary for the proper YM implementation of. • Adequacy of technology to information needs.

2. Demand forecast.

2.1. Analysis of supply.

• Budget Analysis.

• Product Characteristics Analysis.



2.2 Competition Analysis

• Identification of competitors and local market characteristics.

• Analysis of market share, market penetration rate, the average price

index and the generating income index.

• Price Competition Marketing Strategies Analysis • SWOT Analysis: Identification of weaknesses, opportunities, threats,

and strengths.

2.3 Analysis of demand • Analysis of external factors or environment.

• Analysis of historical data.

• Identify patterns and sources of reservations. • Identify determinants of the demand.

3. Segmentation demand

• Determination of the segments.

• Analysis of the contribution of each segment to benefits.

• Election of segments.

4. Setting the fee structure

• Determination of price for each segment according to the company (cost

/ benefit) and the market (demand elasticity, consumer and competition).

• Establish restrictions and limitations on the application of discounts

rates.

• Rate differentiation through product differentiation using physical

attributes and service packages.

5. Capability Distribution

• Establish the capacity for each segment.

TACTICAL LEVEL



6. Calculating and updating reservations limits

• Monitoring of reservations (pick up).

• Monitoring denials and no-shows.

• Evaluate changes in demand over time. • Review the allocation of rooms to different segments as reservations are

being made and make necessary adjustments and updates (close or

open rates, etc.).

7. Acceptance or rejection of reservations and sales • Calculation of displacement.

• Avoid moving the most profitable business. • Implement Crosselling and Upselling policies.

8. Day to day Evaluation-monitoring and correction of YM strategies

• Quantitative Evaluation (income, price, occupancy, profit).

• Qualitative evaluation of YM (customer satisfaction).

• Convey information to staff.

• Support and recognize employees.

• Correct deviations.

Source: YM implementation model by Figueroa, Talón and Vacas (2008).

First is the strategic level, which is structured in five phases:

Developing a Culture of YM (1) agreed with the first model of Jones and Hamilton

(1992), according to these authors it is a pre-implantation phase and is considered

an essential part of the process. YM application has important differences with

respect to traditional hotel management (Donaghy et al., 1997), among which

stands out: the change in strategy (traditional management based on maximizing

the occupancy and YM strategy based on the maximization of income), the

decision-making method: the frequency (sessions carried out during periods

weekly, fortnightly / monthly or annually), along with the scope (appointment of a

team) and analysis of information (unconstrained demand). It is at this stage



where training is essential in the transmission and understanding of this

philosophy among staff. As discussed above, there must be a YM culture in the

company to make clear to customers, through adequate information, that the

practices arising from YM can obtain the maximum benefit for the company and

the customer. According to Yeoman and Watson (1997) highlights the importance

of human resources as a key element to achieve the successful implementation of

this philosophy. It has also been important to incorporate customer information for

the key objective of customer satisfaction considered a part of the YM culture and

the incorporation of technology to the needs of information.

The second phase includes the Demand Forecast (2), almost all authors call their

second phase "demand analysis", but in the proposed model the bid competition

analysis and demand is taken into account, since the aim of YM is to forecast the

demand.

In phase three we find Demand Segmentation (3), similar to almost all proposed

models, although it disagrees with the model proposed by Jones and Hamilton

(1992) for placing it before pricing, when Figueroa, Talón and Vacas (2008)

considered it to be pre-pricing. This model incorporates MSPA or CPA; this

analysis must be done before segment election and should be taken into account

in the budgeting phase.

We now approach fixing the rate structure (4), taking into account the analysis

carried out in the second phase (supply, demand and competition), in the hotel

industry price differentiation is done by market segmentation. According to

Figueroa, Talón and Vacas (2008) hotels have at least three distinct segments

such as groups, leisure and business customers. Urban hotels have a

segmentation of more than ten different segments. A differentiated rate is

assigned to each segment and rates have an assigned code (it is common to find

it in airlines rate assignation Class-B or Class-Y).



Distribution Capability (5), this fifth phase is introduced in almost all previous

models. It lies at a strategic level, as it is done in the long term, due to the difficulty

of making accurate forecasts of capacity limits it must be continuously updated

(opening or closing prices) in terms of demand, but this will take place in the sixth

phase and it will be at an operational level.

Second is the operational or tactical level, which is structured by the last three

phases:

Calculating and updating the reservation boundaries (6), this phase updates

the allocation of rooms according to the behaviour of demand. According to

Chavez and Ruiz (2005) in this phase demand forecasts should be analyzed to the

information available at present, so that they reflect changes in the environment

not previously considered. Once updated demand forecasts, they are compared

with the evolution of real demand and adjustments are made, if the actual demand

exceeds forecast demand you can rise the price of rooms, introduce restrictions

(minimum number of nights, weekends), on the other hand, if actual demand is

lower than the anticipated demand you can reduce higher prices and try to attract

customers from price-sensitive segments, where you can offer promotions and

packages to Low Cost price sensitive customers (Jones and Hamilton).

Acceptance or rejection of reservations and sales (7), at this stage is where

the displacements are calculated and based on results reservations are accepted

or denied. Upselling policies should be implemented (selling a service or product

more advanced and sophisticated) and Crosselling (selling more services or

products which are complementary to those the customer is consuming or intends

to consume) all to maximize sales for it is the goal of this phase. This stage is not

recorded in any of the models formerly mentioned.

Finally, the eighth stage is called Evaluation-Monitoring and Correction (8) daily

YM strategies, the assessment is collected in the first, second and fourth model,

otherwise there is nothing on corrections of process deviations and it is only



introduced by Emeksiz et al. at its fifth stage "monitor and review of YM

strategies." Figueroa, Talón and Vacas propose that the assessment should be

both quantitative and qualitative according to of Emeksiz’s et al model.

2.4. Case study: Yield Management Implementation in the

Community of Madrid

In the Spanish context the latest research on implementation of Yield Management

in the hospitality industry was conducted in the Community of Madrid. The

research was conducted in 2006 and was directed to three, four and five star

hotels of the towns of the Community of Madrid who had more than 35,000

inhabitants and an onset activity former to 2006 (Figueroa, 2008). The study data

showed that, 98% of hotels believe they had launched YM activities; 75% had the

Revenue Manager figure in the hotel, and in 74% held weekly meetings between

the Revenue Manager and other departments, being these hotels those above 401

rooms. With respect to the use of specific YM software, only 13% of hotels have

any, the reason for this low percentage is due to the high costs of computer

application and that hotels must have a minimum size so there can be a return on

the investment. 100% of the chain owned hotels are involved in YM, while only

50% of independent Hotels have it implemented. Similarly, about 78% of chain

owned hotels have a Revenue Manager, while none of the independent hotels

have this figure. 76% of the chain owned hotels holds weekly meetings, while

independent hotels do so in only a 25% and finally, only a 13% of hotels belonging

to hotel chains have any YM software. Five star hotels have more specific

software available compared to three and four star, by increased competition and

economies of scale, the other hotels use other less expensive procedures, such as

Excel spreadsheets. It was also found that as the size of the hotel increased, YM

implementation and specific software increased. The study shows that 71% of

hotels under fifty rooms were engaged in YM; above fifty rooms this practice is

implemented by 100% in hotels of the city of Madrid.



Very positive results were obtained, for most companies used some of the YM

activities (differential pricing, specific rate structure, regular meetings, forecasting,

market segmentation, etc.), but performing certain actions does not involve the

actual implementation of the philosophy in the company, so there are still many

hotels that do not have a price management philosophy and that this is due to a

number of assumptions; according to Figueroa (2008), the fundamental is the

existence of a YM culture in the company, on the other hand, it has been

investigated in former studies (McMahon and Donaghy, 2002), but although it is

found that hotel managers have a higher knowledge on the YM concept they do

not clearly know all the strategies. It does not only consist in rising or lowering

prices in distribution channels, a YM process is much more than that.

Both studies are based on three, four and five star hotels, for YM is more common

is large hotels as they present a variable demand in price segmentation, lower

category hotels often have lower sizes and therefore do not have the same

characteristics as the large ones.

As mentioned the study carried in 2006 was in the whole Community of Madrid

being the later 2009 just from the city of Madrid, the reasons are:

The city of Madrid shows a higher concentration of three,four and five star hotels

than the whole community of Madrid. It was observed there were low proportions

of independently owned hotels while there were large amounts of chain owned

hotels in the Community of Madrid that showed the same behaviours and

management as hotels in Madrid city. Many of the hotels of the Community of

Madrid have low capacities, others belong to lower categories and most of them

belong to “low cost” hotel chains so it wa decided to concentrate the study on the

hotels in the city of Madrid. Between both studies there are the following

differences: it shows time differences for one study was conducted in 2006 and the

other in 2009. The first study is centered on the Revenue Manager figure, if the

RM team holds meeting with other departments, if they have computer YM

appliances, and if they perform YM actions. All these points are classified by hotel



capacity and by different categories (three,four and five star). For the study nine

fundamental variables have been set for a correct YM implementation, through the

research of different models of implementation, the questions on the first study

have also been considered.

As for the economic benefits, according to Talón (2009) to verify the economic

impact of YM implementation is very difficult, since it is difficult to isolate the

impacts that other factors may cause on the result. It should analyze long intervals

of time and should collect data from a minimum of three years, before and after

implementation (Jones, 2000). The indicators used to measure the economic

impact are: Average occupancy (OR, Occupancy Rate), Average price (ARR,

Average Room Rate, or ADR, Average Daily Rate), revenue per available room

(RevPAR, Revenue per Available Room) and the profit or gross operating margin

per available room (GovPar, Gross Operating Profit per Available Room).

Literature offers the following results: An increase in rates between 3.5% and 5%

in the first eleven months (Goymour and Donaghy, 1995) and 5 to $ 10 more per

night (Rowe, 1989). These are data from international markets, while the Spanish

hotel industry, for the time being, have no figures to show the economic benefits

that arise from the YM practices.

Apart from the economic profits we find corporate benefits. First of all, it increases

the knowledge on customer behaviour (mode of action and perception of value,

Chavez and Ruiz, 2005), how to optimize information management (allowing

increased efficiency in handling data and creating demand estimates to facilitate

the adjustment of prices) and forecast the displacements reservations can cause

(Jones, 2000). Secondly increased knowledge of supply and competition,

improves the decision-making process, allowing more flexible workforces and an

improved image of the hotel (Chavez and Ruiz, 2005). And with regard to staff it

increases motivation, training, expertise and speed of reaction.



For all these reasons, arises the need to have a greater knowledge of the practice

of this philosophy, thus making a new investigation that would reveal the actual

practices carried out and the degree of implantation in Madrid’s hotel industry.

Chapter 3: Research Methodology


CHAPTER 3

RESEARCH METHODOLOGY

The previous chapter presented a theoretical review and conceptualization of the

interrelated studies and concepts tied to the research question of the study

formulated as “the degree of implementation of YM in three, four and five stars

hotels in Madrid”. This Chapter describes the main research tools and data

collection methods used to achieve the aim of this Master Thesis and the rational

for the study design. Results, detail discussions and findings from the primary

research that will be presented later.

3.1. Approach to the study

In the study the method applied has been the hipothetic-conductive, which

consists in a theorical revision in which is deducted a contrable consecuence in

reality and where observations made help corraborate the theory. First must be

explained what a hipothesis is. “A hipothesis is a statement or proposal that has

not been checked regarding a factor of phenomenon which is of interest for the

researcher.” (Malhotra, 2004). In which the results obtained through research and

theorical development are utilized as new points from which to work ahead. These

results are generalized, analyzed, summarized and combined in different ways to

find possible explanations with basis, for new facts discovered as for the results

knowned in advance.

3.1.1. Hypothesis

After the revision of literature it is observed that according to Orrkin (1988) “the

main goal of YM system is to maximize the property’s yield by obtaining a revenue

goal that is as close to the potential revenue target as possible”. According to

Brotherton and Mooney (1992) and Forte (2000) “service organisations have been



trying to maximize their revenues for many centuries. The only difference from the

situation in the past is that organisations now aim to improve and manage their

revenues in a more efficient and professional manner with the help of advance

computerised systems”. There are affirmations such as, they produce an increase

of a 3% to 7% in the incomes and an increase benefits up to a 50% (Jones, 2000)

or produces increases of incomes around 2% to 5% (Campa, 2007).

The hipothesis set out in the study is to know whether YM practices positively and

directly affects profit maximization and business management in three, four and

five star hotels of the city of Madrid.

3.1.2. Research Question

It is a fact that the practice of YM in the hotel industry generates very positive

impacts on economic profits and business benefit, but, as we mentioned earlier,

we cannot prove that this is the case in the Spanish hotel industry nowadays. The

main matter of this research is to evaluate and analyze the role of the hotel

industry and how hotels apply the YM process.

The specific objectives it proposes is to identify:

• The degree of implementation of YM in three, four and five star hotels in the

city of Madrid.

• To show if YM culture or philosophy is incorporated in the YM process.

• To know the main obstacles that hotels have when applying YM.

3.2. Proposed Methodological Approach

John and Lee (1998) noted that research is to discover and understand the human

environment and it is a basic activity because all individuals must recognize their

world and understand it enough to adjust to its changes. Also, Elias (1986, in Veal,



2006) suggested that research is to make known something unknown to human

beings and to improve human knowledge.

In this paper it is essential to determine the variables or basic parameters involved

in the process of YM for proper implementation, for this we will have to formulate

an implementation model, after a literature review and an analysis of models of

implementation of various authors as Jones and Halmilton (1995), Donaghy and

McMahon (1995), Jones and Kewin (1997), Yeoman and Watson (1997), Emeksiz

(2006) and Figueroa, Talón and Vacas (2008). Taken as the implementation of a

YM model that proposed by Figueroa, Talón and Vacas (2008) which is based on

the models mentioned above and where others are proposed as detailed below.

(See table nine).



Table 9. Yield Management philosophy Implementation model

Source: YM implementation model by Talón (2009).

To this respect, researches play important roles in throwing light on our lives. Also,

tourism research has its roles for both academic study and its applications to the

tourism and in special hotel industry. The level of commitment of each hotel to

these activities will provide a thorough understanding of the YM implementation

degree.

3.2.1. Secondary sources

Research is a systematic way of answering questions about the world and every

research project needs to confirm its research methodology before it is formally

carried out (Reaves, 1992). The research methodology includes research

philosophy, approaches, and data collection methods, etc. Among data collection

Strategic Level

Operational Level

• Development of a YM culture.

• Analysis of supply, demand and competition.

Supply: Product and Budget.

Demand: Forecast.

Competence (Benchmarking).

• Segmentation of demand.

• Fixing a rate structure.

• Distribution of capacity.

• Monitoring of reservations (pick up).

• Calculating and updating reservation boundaries.

• Acceptance or rejection of reservations.

• Sale.

• Evaluation.

• Corrective Measures.



methods, there are two different sources of information: primary and secondary

(Walle, 1997, in John and Lee, 1998). Secondary data is existing data gathered by

others for some purposes (Veal, 2006). Jennings (2001) states that secondary

data are materials from previous researchers and authors, which include raw data

and published summaries such as minutes of meetings, broadsheet daily

newspapers, and government statistics, articles, etc.

The main advantages of secondary data lie in the broader analysis of social

condition rather than an individual data subject (Finn et al, 2000). Also, secondary

data provides comparative and contextual data by saving time and money

resources (Saunders et al, 2003). On the other hand, secondary data has some

weaknesses such as a lack of complete knowledge of the document that the first

researcher produced, since the previous research was conducted with different

objectives, the valid data might be out of data compared with the current market

(Jennings, 2001). Nevertheless, collecting the secondary data takes place first

since it provides more ideas and more extensive information that might be needed

in research before the primary data starts (Saunders et al, 2003).

As Finn et al (2000) claims literature review is the process of research exploring

the existing literature to ensure what has been written or published on a chosen

research topic, how research has been conducted and how this affects the current

research problem, secondary data was collected in the literature review part for

this Master Thesis.

Moreover, for the determination of the YM implementation model variables

according to Figueroa, Talón and Vacas (2008), later was performed a Delphi

questionnaire aimed at experienced YM teachers at Spanish universities and to

RM from important national and international chains on October-November 2008.

The Delphi technique helps reduce bias in data and keeps any person from having

undue influence on the outcome. Other authors (Green and Hunter, 1992; Ziglio,

1996) recognize the cognitive value of the Delphi analysis as an effective process

of collective wisdom and knowledge extracted from a group of experts in the field.



According to Pulido (2007), "Delphi technique is applied when necessary to

contrast and combine individual arguments and views in reaching decisions

unilaterally not assumable. It is conceived as a technique to cope with complex

problem solving, in which it is necessary to have the knowledge of experts than

can generate intense and qualified ideas".

Its basic approach is to collect expert opinions anonymously using questionnaires,

analyze them and resubmit a new questionnaire, which contains a prior use of the

results of the first information gathered, so that they can change their minds if they

find it necessary (controlled feedback). The procedure is repeated in successive

rounds, usually two, until they refine the answers and arrive at the convergence of

responses on the occurrence of a series of events. The core idea is that “group”

knowledge is better than the one expert in areas where accurate information is not

available. Replaces the discussion and direct questioning by a sequential program

of individual questions to a panel of experts. Its salient features are anonymity,

"feedback" “group” response and the tendency to consensus (Kaynak and

Macaulay, 1984).

Delphis questionnaires were conducted by Professor Pilar Ballesteros Talón,

Professor, Universidad Rey Juan Carlos de Madrid (Spain), prior to this

investigation. The process of the questionnaires consisted of two phases: the first

phase was to send questionnaires to the respondents, who were a total of ten

experts (which will continue its entities in anonymity) to assess the importance of

the variables that affect the YM process.

After analyzing the results of the questionnaires in which they had participated, the

second phase was to re-evaluate their responses taking into account the average

rating of all respondents, and providing a new column to modify their new

assessment. Furthermore variables given by the respondents were also

introduced. After the final analysis of the assessments presented by the experts in

this second phase were determined variables involved in the process, concluding



that it was appropriate and feasible for achieving the stated goals, which

subsequently served to create the questionnaire. (See Delphi questionnaire in

Appendix).

3.2.2. Primary sources

Primary data is new information collected by the researcher as first hand data for

the specific purpose (Veal, 1997; Jennings, 2001). According to Blazter et al

(1996), primary data is divided into two types: quantitative and qualitative as.

Quantitative approach contains statistical analysis to draw conclusion and by

contrast, qualitative method is associated with small-scale word description with

holistic perspective (Veal, 1997). For this Master Thesis, the researcher applies

the results obtained in a research performed during 2009 while studying

methodology in first year of International Tourism Management Master. The

researcher will employ quantitative approaches; by using the collection of

questionnaire survey in order to quantify data and generalize results from sample

to the population about, positive impacts on economic gain and business benefit,

the actual degree of YM implementation in three, four and five star hotels from the

city of Madrid, and to what degree YM culture or philosophy is incorporated in the

process, etc. After data collection, these will be processed using SPSS software

for further analysis and make conclusions.

3.3. Quantitative research process

3.3.1. Questionnaire design

Questionnaires are the most common type of form used for primary data collection

in tourism (Cooper et al, 2005). According to Saunders et al (2003), there are two

types of questionnaires: self-administered and interviewer administered. In case of

self-administered type, respondents fill in the questionnaires themselves, which is



efficient in terms of research time and effort so that this type of questionnaire will

be employed for this research.

According to Saunders et al (2003), there are two forms of questions: closed and

open questions. The former ask respondents to choose answer from given options

so that it is easy to answer because minimal writing is requested. But, it can lead

to bias due to given options, which is likely to be researcher’s opinion instead of

respondent’s one. Meanwhile, open questions demand respondents to give

wording answers. But, it can also lead to reduce response rates (Denscombe,

1998). Therefore, most of the questions in this research questionnaire are closed

ended to obtain higher response rates; 111 close-ended questions and one 22

open ended question.

3.3.2. Questionnaire Analysis

We now want to analyze the structure of the questionnaire, which has been

divided into four different sections:

Socio-demographic.

In the first part, we define a previous section in the questionnaire that requires

respondents data, such as: the name of the establishment, name of respondent,

position in the establishment, location, e-mail and phone to have perfectly located

the questionnaire and at all times know what establishment belongs to in order to

correct possible errors and wrong information given.

It introduces a matrix question marked as question C1, which serves to clarify, in

order to study if hotels apply YM or not, key to continue with the questionnaire if

so, or end the process if not. Question C2 will provide the data on since when has

the hotel implemented YM. According to Jones (2000) "it should analyze long

intervals of time and should collect data for a minimum period of three years,



before and after its implementation". This will reveal whether the application is real

or not.

The questions P1 to P6 of the previous block have been aimed to know the

specifics of the hotel respondent. Those variables may therefore be defined as

socio-demographic variables. They are defined as:

• Number of stars: three, four and five stars.

• Size of hotel: number of bedrooms, allocation.

• Management Model: ownership, leasing, franchising, management.

• Chain owned or independent.

• The chain, the hotel or both perform YM management.

• The person responsible for YM in the hotel: director, housing director, sales

director, booking manager, receptionist or other to be specified.

Only note that question P4 skips to P6 if the hotel is independent, since question

P5 refers to the different alternatives of participation in the management when the

hotel is owned by a hotel chain (Management controlled entirely or partially by the

chain, either partially or totally by the hotel). P8 to P13 refers to culture issues and

resources they have or are employed in YM processes, which will be discussed in

the next section.

Yield Management Application.

Following this introductory block, the questionnaire was divided into nine sections;

these are the variables defined above by the implementation model that was

chosen for application and the results of the Delphi questionnaire mentioned

formerly, which make up a battery of questions from one to 77. With this battery of

questions we seek to know in detail the uses and specific applications of YM in the

respondent hotel.

YM Culture and Resources is the first section, which is divided into three sub-

blocks; two before the battery of questions and a third where we have three



questions which are the beginning of the battery of questions: in first sub-block the

purpose of the three questions is to ascertain how employees and customers see

YM Culture. These questions are answered with a Likert scale, one to five as

considered, quite agree or strongly disagree.

The second sub-block refers to resources used in the YM process; two questions

seek to know if there is a unique figure in charge of YM implementation and if

there is specific software. Is it answered dichotomously (closed questions) and

regarding software is requested name and year of purchase, as qualitative data.

The third block are three dichotomous questions (closed questions) by these three

specific questions about YM culture, it pretends to know whether the respondent

has had support of his superiors, if the RM team has received previous training,

and if the person or team are updated with regards to YM issues.

Forecast, is the second set of questions, including from question four until the 11

inclusive. They have tried to find out what kind of data is considered when making

a good YM forecast. Therefore issues asked are: historical data, cancellations,

denied room, future trends, future reservations forecasts or medium revenue per

room, among others.

Competitive analysis is the third section that extends from the 12 to 17, with the

aim to study what kind of strategies are used to analyze competition, either

directly, as in search engines, distribution channels, shoppers, bench. The later

questions in this section, more technical data is requested as related to ARI, MPI

or IRG.

Segmentation of demand is the fourth variable question ranging from 18 to 19.

This block seeks to know if hotels apply YM processes in demand segmentation

tasks and if so, find out how and to what degree it is done. They are asked how

many segments are accounted for, type, origin of segments, purchasing behaviour

of each segment, etc.



Budgeting is the fifth variable, consists of only two questions, the 20 and 21,

where it is taken into account whether the budgeting is done by market segments

and if RM projected demand budget’s is considered.

Pricing is the sixth variable comprising questions 22 to 34, where it is expected to

know the YM team’s price techniques application and the circumstances taken into

account when deciding price setting, like events to be held in the city, if they

differentiate rooms by adding attributes that do not cause an increase in capital

costs, etc.

Distribution channels are the seventh variable, which is composed by only three

questions ranging from issue 35 to 37. The search is to find if distribution channels

are analyzed, if they recognize which are the most profitable channels, which are

better placed and if you cannot find cheaper rates in other distribution channels

better than those offered on the hotel’s website.

Reservation Update and sales limits, is the eighth variable, this block ranges

from question 38 to 45, analyzing what factors are taken into account in

establishing reservation and sales boundaries when applying the YM process,

such as acceptance or rejection of reservations based on the length of stay,

season, volume of reservations and reservations accepted when the benefits

produced are greater than the benefit of an extra room available, and other

technical data such as, if they are engaged in overbooking activities, Upselling and

Crosselling.

Evaluation is the ninth variable of this last block and ranges from the question 46

to 50. This seeks to learn the techniques of evaluation in the implementation of

YM, through daily review of results, comparing the actual with the budgeted as

well as whether hotels have an incentive program for employees who apply up

selling or Crosselling and will in turn show whether YM culture is integrated into

the company.



Economic Data

This section asks for data concerning hotel performance from the year prior to YM

implementation and two years after implantation, it must provide the percentage

change in the data. The information is requested on the basis of a percentage of

real or approximate occupation, price, revenue per available room and gross

operating margin. These data will clarify the positive effects of YM on the

economic returns of hotels using this activity.

Benefit Analysis, challenges and obstacles in Yield Management implementation.

To finish analyzing the questionnaire the respondents are asked to assess

benefits, challenges and obstacles that have occurred in the hotel by the

application of YM. A Likert scale has been used, where one strongly disagrees

and five strongly agree in the benefits section. In the difficulties and obstacles

section one is little important and five very important.

To conclude the analysis of the questionnaire a glossary has been included to help

clarify some of the concepts objects of this study that may sometimes be unknown

to the users of the study. (See questionnaire in appendix).

3.4. Sampling and sample size

Sample is a subset or subgroup of the population, while the sample size is the

actual number of subjects chosen as a sample to represent the population

characteristics. Sampling is the process of selecting items from the population so

that the sample characteristics can be generalized to the population (Jennings,

2001). To guarantee the representativeness of the sample, the researcher must

make sure that it is random. In random sampling all members of the population

have an equal chance of being included in the sample (Veal, 1997).



3.4.1. Design of the sample frame

The sampling frame of departure is a total of 180 hotels according to Tourspain

census of 2009. The field of research are the hotels the city of Madrid (Spain).

Companies have been differentiated by categories: hotels of three, four and five

stars.

The subject of the study in addition to hotels, are Revenue Managers and Hotel

Managers, in their absence an order of descending hierarchy was applied. Since

the objective is to study the implementation of Yield Management and Revenue

Managers, and if they are built in the hotel or are at a corporate level in hotel

chains and if so, who is the representative figure for YM in the hotel, if it exists.

3.4.2. Sample size and error level

The initial sampling frame, comprises 180 hotels, a theoretical sample has been

selected, comprising a representative population size of 160 of hotels in the city of

Madrid. The type of sample that was used for this selection was systematic

random per extract by type of hotel category (three, four and five stars). The

theoretical sample size has an error level of less than or equal to 5% for a

confidence level of 95.5%. Following, table ten shows the distribution of total

population according to category of hotel along with the count and percentage of

distribution of each category.



Table 10. Population Distribution by category

Source: own elaboration.

As shown in table ten, four star hotels are, the most representative, reaching a

population size of 93 units that represents 58% of the total sample, three star

hotels with 51 units represent 32% of the total sample, and finally 16 five star units

represent 10% of the total sample.

3.4.3. Effective final sample

At the time of closure of the fieldwork June 1, 2009, we had received a total of 84

questionnaires; this represents a response rate of 52.50%. The downstream

purification of records found three questionnaires did not meet the minimum

requirements, so the final effective sample was reduced to 81 questionnaires, a

response rate of 50.63% on the total sample. 79 hotels abstained or refused to

collaborate in the study, representing a non-response rate of 49.37%.

As shown in the following table 11, four star hotels had a high response rate in the

effective sample with regards to the theoretical distribution, is represented by

60.22% followed by five star hotels with a response rate of 56.25% and finally

three-star hotels that reported a response rate of 31.37%.

Category Theorical Sample Sampling

Percentage

Five 16 10%

Four 93 58% HOTEL Three 51 32%

160 100%



Table 11. Response rate

Category

Theorical sample

Sample Effectiveness

Percentual Response rate

Five 16 9 56,25%

Four 93 56 60,22%

HOTEL

Three 51 16 31,37%

160 81 50,63%

Source: owned elaboration.

3.4.4 Bias and error level

At this point it is worth asking about the possibility of finding bias in the sample

data. If we take the theoretical composition of the sample as the absolute truth, it

is concluded that there is a significant bias favouring three star hotels, since they

are overrepresented in detriment of four star hotels by its final weight in the

effective sample. As shown in the following table:

Table 12. Bias and error level

Category

% Theorical

Sample

% Effective

Sample Differentiation

Five 10% 11% -1%

Four 58% 69% -11%

HOTEL Three 32% 20% 12%




Having to correct the size differences is a common need in methodological

research, being weighting the most common measure. After the differences shown

in the table above, it is considered necessary to weigh the results because there

are fundamentals to assume that the quality of the sample collection may have

been affected by any bias resulting from the decisions taken during the fieldwork.

(See table 13).

Table 13. Weighting Factor

Category

Sample Effectiveness

Percentual Response rate

Five 8 10%

Four 47 58,1%

HOTEL

Three 26 31,9%

81 100%


After obtaining the weight factor we see how new values are distributed, being first

the four star hotels with a 58.1% response rate, followed by the three star 31.9%

and finally five star hotels with a 10%. As a result of the small sample size and

high level of error, we consider taking with extreme caution the results crossed by

different variables.

3.5. Fieldwork: Protocols and results

This section describes the methodology followed during the fieldwork (protocols

applied, type of questionnaire, etc.) and the final results of its application.



3.5.1. Pre-test questionnaire

Before starting the fieldwork, there has been a pre-test of the initial draft of the

questionnaire for possible errors in its approach to the subject, which would lead to

an ambiguous interpretation respondent of the surveyed questions. Four industry

experts were surveyed in order to close the questionnaire. Professionals

conducted the questionnaire designed it in this first phase, after which they

outlined their assessments, concluding that it was appropriate and feasible for

achieving the targets. This pre-test phase has helped refine the questionnaire and

correct errors difficult to appreciate at first. It was noted, that many of them had

very different profiles in terms of professionalism and training or address gaps in

hotel jargon technical terms, a glossary has been included (above) with common

definitions that has served as a tool for understanding the questionnaire. The

duration of each interview with hotel industry experts was around 20 minutes.

Upon completion of the pre-test the fieldwork began.

3.5.2. Fieldwork protocols

The date of completion of fieldwork has ranged from April 1, 2009 until its

completion on June 1, 2009 (for teaching requirements.) As of September 2009

the coding stage and the use for statistical data have been collected in the

fieldwork. The type of interview that has been applied in most of the sample is self-

administered questionnaire; the procedure for sending and receiving

questionnaires to the sample holder was as follows:

• Phone calls to verify contact details of Revenue Managers.

• Submitting cover letters via e-mail.

• Sending questionnaires via e-mail to the Revenue managers.

• Telephone contacts to encourage participation, repeated until a

sharp negative.

• Receipt of the questionnaire via e-mail.



It has used two ways to complete the questionnaires, via e-mail and telephone.

The questionnaire has been sent to the person responsible for YM management of

each of the different hotels. On the other hand, centralized reservations have been

considered, all those belonging to hotel chains where YM management was

centralized. Finally, the survey has had no commercial purpose, information

collected is protected under the governing law of statistic government

confidentiality, not being able to discuss or release unless in a numeric and added

way to guarantee the anonymity of respondents.

First stage, April 2009: during the first days in collaboration with the Association

of Hoteliers Madrid, we emailed a questionnaire and cover letter with a sample

holder for hotels to comply with the requirements of the study (hotel name,

category, e-mails, telephone, named revenue manager, etc.). The cover letter

provided a contact number for advice should they want to verify the authenticity of

the study. A week later, the telephone contacts were initiated with each hotel

serving as a reminder and to find out the state the survey, had it been received

and was it being completed or if they did not want to collaborate in the study.

Second stage, May 2009: during this second stage, given the evidence that the

study had a low response rate, we proceeded to contact the hotels implied in the

survey via telephone, in order to close out the approaching fieldwork as far as

possible making the actual sample as similar as possible to size of the sample

theory. At this time of fieldwork there were some elements to address the reasons for the low response rate to the questionnaire. In most cases, when the

respondent was questioned over the telephone pointed to the lack of time to

gather information to answer the survey and asked for a longer period of time.

Finally there was a cleansing of the questionnaires received, for the acceptance or

rejection of those who did not meet the minimum requirements.



3.5.3. Issues occurred during the fieldwork

Here are highlights on several incidents and problems experienced during the

fieldwork, so that they qualitatively illustrate the difficulties we faced during this

investigation.

The first issue arose when trying telephone contact with managers and Hotel’s

RM. Access to them has been very difficult in most cases because they are people

of high positions and they alleged a lack of time to complete the survey. The large

size of the questionnaire has been in itself a problem in carrying out fieldwork,

since in several cases; managers did not have the time needed to answer the

survey.

We found two types of non-respondents qualitatively different:

• On the one hand, owners of three star hotels are unfamiliar with hotel

management jargon (in this case concerning YM) and considered that the

greater part of the questionnaire "had nothing to do with them”.

• In addition, hotel and revenue managers, whom were very difficult to reach

often apologized for their tight agendas, the strategic nature of some of the

requested data and, in some cases, alluded to excessive saturation surveys

from multiple institutions.

Another scenario occurred during the study, several investigations were launched

simultaneously from the University Rey Juan Carlos. These facts caused problems

when asking for hotel cooperation, since several of these investigations, were also

addressed to hotel managers, who after collaborating in completing relevant

questionnaires flatly refused to cooperate again.

On the other hand, certain difficulties arose with those hotels belonging to chains.

In this sense, most hotels have not provided any information about applications or

YM actions carried out within their hotels. It has therefore been necessary to



contact the head offices for the requested information, the latter being highly

heterogeneous and unrealistic.

On the other hand, it highlights the problems experienced in relation to some of

the questions posed in the questionnaire. An example has been the case in

question number 45, which was formulated in a negative way, "You can not find

cheaper rates on other sites other than the hotel’s", attributing a dichotomous

response (yes / no) so that the same approach led to the confusion both the

interviewer and the interviewee. Equally there has been misunderstanding issues

concerning the difficulties and obstacles, as in the approach, it lacked a

comprehensive and structured question. Given the ambiguity, to which these

issues have been subject, we believe that the results may not be true or "real".

Finally, we make special mention of the difficulties experienced in the collection of

data relating to profitability. The lack of confidence of the hotel managers to play in

facilitating economic data, which has led to obtaining a very low or almost non-

existent response rate in relation to these variables. In addition, the limited data of

the heads of the hotels have been, in the vast majority of cases, approximate

and/or rounded figures. Given this situation, it was decided to exclude these

variables of the research study.

Chapter 4: Findings and Analysis


CHAPTER 4

FINDINGS AND ANALYSIS

In this chapter, we gather the analysis of results, after the completion of the

fieldwork, which ended June 2009 to hotels in the city of Madrid. As proposed in

the methodology we used a secondary data analysis (literature, articles, etc.) For

the theoretical framework for primary data analysis we used a quantitative, self-

administered survey method. SPSS has been used for the processing of the

results of primary data.

The following will present the results obtained, first a descriptive analysis, second

a multivariable analysis.

4.1. Descriptive data of effective sample Within the effective sample we found a number of socio-demographic variables

that allowed us to obtain more precise information regarding the hotels under

study. Among them are the following: hotel category, hotel size, YM applied as

hotel management /or not, year of YM implementation, management model used,

independent hotel or chained owned hotel, having a YM figure within the hotel.

The following will develop each socio-demographic variable block.

4.1.1. Socio-demographic analysis

Regarding the different categories of accommodation, we observed a large

presence of four star hotels, with a 58.1% representation of the effective sample.

Followed, by the three hotels, although their representation is lower, 31.9% of the

total. Finally, five star hotels make up only 10% of the sample under study. Figure

one shows each hotel categories’ response rate analyzed in the investigation.



Figure 1. Hotel category


As for the size of the hotels, they have been grouped into three blocks, depending

on the number of rooms they have. We speak, therefore about small hotels,

medium and large hotels. The reason for this grouping was due to the multiple

responses from hotels giving us many different values. Thus, what we will find is a

much clearer and sorted result that will allow us to draw some conclusions.

To make this division, 34 rooms has been considered as minimum data and 790

as maximum data, being this last value, an extreme value for only one hotel

exceeds 400 units of accommodation. Three intervals were created: small hotels

of up to 100 rooms, medium hotels, from 101-250 rooms and large hotels, those

having from 251-790 which is the last numerical data record.



The following table shows the distribution of the number of rooms according to

category and size of hotel.

Table 14. Hotel size Hotel size Small Medium Large Total

Three star 15 9 2 26

Four star 11 31 5 47

Hotel Category

Five star 0 3 5 8 Total 26 43 12 81


Data shows that average size, which is the interval from 101 to 250 rooms, is the

most representative for four star hotels followed by three star hotels which are

characterized by small size, also having medium-sized hotels although less

representative, five star hotels are located in the interval represented by a large

dimension of 251-790 rooms. We can say that three star hotels in Madrid are small

to medium size; four star hotels have average size and five star have a large size.

As regards to the application of YM, only two of the hotels surveyed did not apply

a YM philosophy compared to 79 hotels that do so, this represents a 98.1% of

effective sample if they apply this tool in their business management.

These are two small three star hotels, which, despite performing certain YM tasks

or functions (according to the survey), do not have YM culture incorporated as a

business management tool. This confirms some of the statements found in

previous literature, which states "most of the hotels perform some of the activities

of YM (such as having differential pricing, a specific rate structure, team meetings

forecasting, market segmentation, etc.), but the implementation of any of these

activities alone, does not involve the actual implementation of this philosophy in



the company, for a certain amount of premises should be given, the fundamental,

in our view, is the existence of a YM culture in the company" (Talón 2009).

Table 15 shows the variable frequency analysis of the YM application in three, four

and five star hotels.


Without any doubt, one of the most interesting demographic variables has been

the date of application of YM in each of the hotels, and that 40.7% of the sample

began to implement YM in the period 2003-2006.

Data confirms a part of what has been exposed in previous literature research,

2006 in Madrid, which stated, "On average YM activities begin in 2003. The

emergence Revenue Manager post and the weekly meetings date from 2004.

However, most of the hotels introduced YM philosophy and software in 2005... "

(Figueroa et al., 2008). Polls show that four and five stars hotels implemented YM

practices from 1999 to 2002 almost in identical proportion as from 2003-2006.

Table 16 describes the distribution with respect to the date of application of YM in

three, four and five star hotels.

Table 15. Applies Yield Management Applies Yield Management Yes No Total

Three star 24 2 26

Four star 47 0 47

Hotel Category

Five star 8 0 8 Total 79 2 81



Table 16. Implementation date of Yield Management Hotel Category Three star Four star Five star Total

Count 2 7 4 13 1999-2002

% of Total 6,3% 21,9% 12,5% 40,6%

Count 2 8 1 11 2003-2006

% of Total 6,3% 25,0% 3,1% 34,4%

Count 2 6 0 8

2007-2009

% of Total 6,3% 18,8% ,0% 25,0% Count 6 21 5 32 Total % of Total 18,8% 65,6% 15,6% 100,0%


We must keep in mind that of the 81 surveys collected, only 36.5% are valid cases

and 63.5% are lost cases (random sample size of the total sample) answered no

to this question, we must take it into account as it overcomes the invalid cases

more than N=60% valid cases, therefore we cannot be certain of the

correspondence of the 2003-2006 period of YM implementation.

In relation to the management model, ownership represents a 46.1% of the

effective sample, followed by renting, with 40.8%, and finally, the management

model depicted by 13.2% of the effective sample, being the ownership and renting

the most common formulas in the model of hotel management in Madrid. It could

confirm that hotels surveyed, are not involved in franchising model management,

however the response rate for this item collection, is valid N=93.8% versus a loss

of values of N=6.2%. This data contrasts other data gathered recently in which it

said: "The Hospitality sector seeks new growth strategies based on management

contracts and / or rental and not so much on property" (Vogeler, 2009). However,

it is considered that the results of the study do not have to contradict the fact that

they are looking for new growth strategies.



Table 17 contains the frequency distribution according to the hotel management

model and type of hotel category.

Table 17. Hotel Management Model Hotel Category Three star Four star Five star Total

Count 9 21 5 35 Ownership

% of Total 11,8% 27,6% 6,6% 46,1%

Count 11 20 0 31 Rented

% of Total 14,5% 26,3% ,0% 40,8%

Count 5 3 2 10

Management

% of Total 6,6% 3,9% 2,6% 13,2% Count 25 44 7 76 Total

% of Total 32,9% 57,9% 9,2% 100,0% Source: Own elaboration

One thing to keep in mind is the fact that the vast majority of hotels in Madrid are

part of hotel chains, like NH Hotels, Sol Meliá, Starwood, Ritz Carlton, etc. Polls

show the independence item or membership to a hotel brand, 78.9% hotels in

Madrid are part of a hotel chain and another 21.1% are independent hotels. In the

next section we shall see, the variable person responsible for YM management,

this variable will be strongly affected by whether or not the hotel belong to a hotel

chain. Figure two shows the distribution according to the independence or

membership to a hotel chain.



Figure 2. Hotel independence


To finish the socio-demographic descriptive analysis, the item addressed is who is

the figure is responsible for YM in the hotel is. Regarding this aspect, the

effective sample reveals that in 56.5% of the hotels the person in charge of YM is

the Revenue Manager, followed by Front Desk Manager or Head of Reservations,

17.2%. As a third responsible for the YM management, was found the figure of the

Hotel manager, with a 9% and Marketing manager with 4.2%. However, one

should consider that 78.9% of the hotels that make up the effective sample belong

to hotel chains, while only 21.1% are independent hotels, in this way, and

considering that almost all hotels belonging to chains have centralized YM

management, it is easy to understand the high percentage of Revenue Managers



detailed above, it means that the same Revenue Manager works with several

hotels at once, therefore each hotel does not have a Revenue Manager on site.

Figure 3. Person responsible for Yield Management


4.1.2. Descriptive analysis of Yield Management variables

When addressing the analysis of the variables involved in the YM process, we find

that the blocks of questions of each variable have high response rates, the items

are characterized by dichotomous questions (Yes or No), the survey showed a

high response rate for Yes they perform YM activities and a low response rate of

No for the performance of some of the YM activities. To summarize each variable,

we proceed to cluster the Yes YM activities responses by summing to find the

possible frequency of population that performs this process, the recoding of each



variable shows that the population responds very favourably to Yes and that there

are very few No’s recorded. Noting this, we recoded the variables and turned them

into percentages to better observe if hotels perform YM and in what proportion. It

must be said that when information is synthesized in statistics, it is a fact that

information is lost, a fact to consider. The following will present the results of each

variable after the analysis of each.

In our first block on YM culture and resources, seen broadly, results show a very

high positive rate with respect to the variables analyzed. It shows that more than

87.9% of the staff in different hotel departments surveyed know and share YM

goals. On the other hand, while in the item referred to whether the guest perceives

as fair price changes, the survey found that 71.6% do "not perceived as fair price

changes" versus 28.4% of "prices changes perceived as fair". The following figure

shows whether they have specific YM software.

Figure 4. Yield Management software




On this block of resources, we have crossed the item, belongs to hotel chain and if

they have software, there has been a valid response N=95.2% and one of missing

data N=4.8%. In item response, whether hotels have specific YM software, data

suggests that hotels do have specific software in a 37.2%, of which 1.3% are

independent hotels and 35.9% are hotels belonging to chains that claim to have a

YM computer application. On the other we have recorded that in 62.8% of cases,

hotels do not have a specific YM computer application, of which 19.2% are

independent hotels and 43.6% are hotels belonging to chains. We can say that

independent hotels do not invest in specific YM software, as for example Rate

Tiger, possibly due to its high cost. However hotel chains do have special

computer application compared to independent hotels, but the non-acquisition of

software is still predominant. Possibly there will be a need for studying if hotel

chains have developed an integrated management tool, which implies some YM

variables.

More than 57.3% of the hotels in Madrid have a full-time YM responsible. Where

54.7% are hotel chains and 2.7% are independent hotels. These results could be

because of their belonging to hotel chains counting with more resources due to

increased funding and the allocation of costs between the various hotels. 42.7% of

the hotels do not have the YM figure implemented.

After the re-coding of the nine variables above, we will post the results. First, the

variable YM culture and resources, shows that 84.7% of hotels surveyed replied

they have YM incorporated in their business management philosophy. While

15.3% of hotels do some things regarding YM but not all.

As for the block associated with forecast, broadly, the results show positive

values, we find that the hotels meet at least 50% of the questions, while 70% of

the populations are above 75% response rates, when replying that they apply

forecast. We also find some variables with missing values, 12.5%, to be

considered. Data shows that most hotels consider their historical data when

forecasting, do pick up, analyze environmental factors and future events.



In the analysis of competition is of N=84.8% of valid values against an N=15.2%

of missing values. 74.4% of valid values respond more than 75% of the questions

in this block, so hotels in Madrid perform tasks of identification of competition,

determining the positioning of the hotel in time (short and long term) analyzing

pricing strategies of competition, measuring the MPI, ARI, IRG and analyzing the

competition periodically. Either being independent hotels or belonging to hotel

chains, no significant differences have been found with previous results, in saying

that hotel chains are the ones who have more YM practices implemented as

business management.

The segmentation of demand shows that 76.9% respond positively to more than

75% of the questions, it reflects that hotels also do market segmentation and

distinguish types, the source, customer’s purchase behaviours, they also know the

contribution of market segmentation to the hotel’s benefit.

The budgeting variable, data shows that 45.7% take into account RM

departments’ demand forecast and the budget is done through market

segmentation. And 40.7% take into account at least one of these two activities,

which shows a high degree of YM budgetary activities. 60.5% of the hotels

belonging to hotel chains based their budgeting RM department demands, while

independent hotels, show that an 11.8% base their budgeting upon RM

department demands. This result seems logical because hotel chains have a

greater force in providing for this department, since it is themselves that mostly

have the Revenue Manager figure involved in YM tasks. (See figure five).



Figure 5. Demand forecasting Revenue Management department


In the results obtained in the variable pricing, we see that all the percentages

obtained are very positive in chains as in the independents. The response was

over 75% of the questions, registering a 87.1% engaged in price fixing, as the use

of differential pricing, price offer "packaged" with other services i.e., prices are

fixed taking into account costs, demand, competition and distribution channels,

etc.

In the item "TT.OO. rate variation and corporate accounts” shows that a 66.2% of

the hotels vary the rates, but 33.8% of cases cannot do so, this reflects that rate

negotiation is not as rigid as in the past and that TT.OO. do not have the

bargaining power they had in the past, hotels manage their room sales quota.



In distribution channels, hotels perform analysis of the positioning of the various

channels then pick the most profitable ones and finally have a hotel website with

the possibility of marketing the product and selling it online. Data shows that

85.7% reported all these activities.

Table 18. Hotel web on-line bookings Hotel web

on-line bookings

Yes Total

Count 16 16 Independent

% of Total 20,5% 20,5%

Count 62 62

Hotel independence

Hotel Chain

% of Total 79,5% 79,5% Count 78 78 Total

% of Total 100,0% 100,0%

Table 18, reveals that both independent and chain owned hotels market and sell

their products through their own website, which reflects that they have developed

internet as a promoting and selling tool to the customer, on the other hand it is

related to the "variation of rates with tour operators” stated earlier, hotels choose

to negotiate with their direct customers through the hotel’s website. Results show

that 20.5%of the independent and 79.5% of the chain owned hotels have this tool

incorporated into the YM management.

In the case of the variable to update the reservations and sales boundaries, shows that only N=73.6% are valid, recording a loss of N=26.4%. This means they

you have not answered the entire effective sample, and that this effective sample

is biased by the response rate. 61.8% of hotels respond with a Yes to this variable

and, if reservations are accepted or denied depending on the season, length of

stay, if they perform overbooking activities, etc.



It shows different results between "accepting or rejecting reservations depending

on the season" we appreciate heterogeneous rates among independent hotels

and chain owned hotels, we see that independent hotels accept or deny seasonal

reservations by 11.5%, yet it shows that chain owned hotels do not in a 44.9%,

data recorded are similar in both cases because independent and chain owned

hotels is performed or not in similar percentages. Five star hotels are the only

ones that do accept or deny reservations depending on the season by almost 9%.

In the item "accept or refuse reservations according to length of stay" is noted that

the hotel chains perform this activity in a 61.8% compared to independent hotels

who do it by 10.5%, also noted in the item "accept or refuse reservations

according to sales volume," is done in hotel chains in a 66.2% and by independent

hotels in a 16.9%.

Data shows that hotels in Madrid accept or deny reservations depending on the

length of stay and the booking volumes and do not operate much according to the

season, except in five star hotels, which reflects that for hoteliers in Madrid there is

not such a marked seasonality in their hotel management.

Finally, the YM evaluation of the process variable has recorded that 85.6% have

responded to more than 80% of the items, thus hotels in Madrid are engaged in

daily review of results comparing the actual with the budgeted, analyzing

deviations and encouraging counter and reservations staff to implement

Crosselling and Upselling techniques. It is stressed that the chain owned hotels

support Crosselling and Upselling by applying incentives to their front-desk and

reservations staff.

The following Figure six shows that only five independent hotels and 45 hotels

owned by chains encourage these practices.



Figure 6. Motivate staff by Upselling and Crosselling

Source: Own ellaboration

4.2. Yield Managment implementation multivariable analysis In the dependence analaysis, obstacles, difficulties and benefits block, analysis of

variance was carried out, which measures the statistical significance of differences

between the dependent variable measures presented in the different groups. The

process for this dependence analysis was to create a new variable, which is the

sum of all amounts; it is reflected in the new recoding of the number of YM actions

the hotel performs.



The new variable (percentage adder) is used as numerical; an analysis of variance

is performed with the benefits to compare averages. One thing to note is that all

blocks of questions have been given the same weight of importance, ignoring the

amount of questions in the different blocks.

In Figure seven it is seen that for a 30.2% of hotels YM is very influential and for a

65.6% it is completely influential, only three hotels disagree not meaning any

difference for the high positive response in increasing hotel benefits by YM

practices. Analysis shows that for hotels that replied that YM is completely

influential in hotel benefits made an average of 66 actions over 77 YM actions.

Following come the development of the mayor actions hotels carry out.

Figure 7. Increase profits




The following are the results obtained by comparing the response of item

"increases hotel benefits" with the added percentage of the actions of the variable

"YM culture and resources”. Data suggests that 100% of the hotels have YM

culture incorporated in business management and value as completely influential

management’s, ownership or chain support when implementing YM philosophy,

and a 90.91% finds it crucial to have a well trained RM team, 88.31% to be

updated in YM in forums, blogs, newsletters.

In the variable of "segmentation of demand" the recorded 88.31% claimed to

have more than four segments, a 77.92% finds it very and totally influential to have

market segmentation by types of activities, seeing the origin of the segments,

analyzing the contribution of each market segment to the benefit and to analyze

the segments that come through distribution channels. Hotels in Madrid find that

the performing correct segmentation of demand favours the hotels profitability.

Over 80% of the hotels performed actions on "analysis of competition", a fact to

note is that there has been many cases where they do not give much importance

to long-term position (more than 12 months) but to short term positioning (less

than 12 months). They do not commonly use tools for analysis of price competition

such as shoppers (rate shopping) or bench. Nor do they measure the MPI, RMI

and ARI, 50% have been recorded as they do perform, the other 50% do not

perform.

As for the "forecast" hotels perform in more than 80% occupancy forecasts, the

correct analysis of historical data, taking into account local events, future events,

knowing in advance the reservations made by each market segment, a good

analysis of the environment and keeping track of the pick up has a direct impact

on increasing the benefit of the hotel.

In the “budgeting” variable 78.3% of businesses believe that the impact of YM is

absolutely influential in increasing the profit of the hotel when engaging the RM

department in forecasting the demand, while those who think it is very influential



only do budgeting on forecasting demand on a 52.8%. In the item "the budgeting

is done by market segment”, the differences increases as in the aforementioned

variables, being a 72.4% those taking actions who consider it totally influential and

only a 28.6% of those who consider it very influential. In summary, those that think

that YM is absolutely influential in the profits of the company are precisely those

who mostly take into account this aspect when budgeting.

In the variable "pricing“, hotels think that taking these actions influences hotel

benefits, results are very similar to previous data on Revenue Manager believing a

90% that these actions are totally influential to increase the hotels benefit, and the

68% of them that think that these actions are quite influential record lower rates

but still quite high.

As for the "distribution channels" the recorded percentages are high 100% of

the hotels think it is totally influential that the hotels received on-line reservations

from their own websites a 93.1% think that is totally influential to analyze the

positioning of the various distribution channels and finally 91.95% consider to

choose the most profitable channels to influence hotel profit.

When it comes to "Limiting and updating reservations and sales" the most

valued by hotels and which are considered utterly influential in increasing the

hotels benefit are in 100% is to have updated information of number of rooms

available, 81.8% to apply Crosselling and Upselling techniques, 90% to carry out

overbooking activities, 80.5% to accept or reject reservations based on length of

stay and booking volume, 94% open or close sales depending on demand

forecast.

In the last variable "assessment" the actions that are taken into account as fully

influential in increasing the hotels benefit are: 100% to assess the benefits

resulting from the application of YM taking into account the average occupancy

rate, price average RevPar, etc., a 88.5% to check daily results, 90.2% to compare

the actual against budget, a 96.6% to analyze the deviations that occur during the



process and 73% to apply incentive schemes for front desk and reservation staff to

encourage the implementation of Crosselling and Upselling techniques.

The difficulties and obstacles block did not provide very relevant data about the

difficulties and obstacles of the implementation of YM in hotels of three, four and

five star reviewed. The results are:

In the average data recorded items of “difficulties and obstacles” range from 2.71

to 3.87 range. After an analysis of variance of a factor by hotel category, data

shows significant differences in the item of "lack of ICT", in three star hotels finding

it a mayor problem for their hotel management rather than for five star hotels that

do have them. We performed Pearson’s chi-square test to see if these two

variables are dependent or independent and the result was that the variables

“hotel category” and “shortage of computer applications” are dependent.

Another relevant fact in this analysis of variance, is related to the item of "the lack

of resources," comparing the categories of five and three star hotels, there is

considered to be a confidence interval of 95%, manifests an average difference in

post hoc test more, less 1.822, being the average 4.27 and 2.44 respectively.

There are also significant differences among four and five star hotels that show

more, less 1.111 in post hoc test with an average of 3.56 and 2.44. Pearson’s chi-

square test was conducted and it observed that the two variables are dependent

on each other. It follows from this that five star hotels use many resources in the

management of YM, compared to four star hotels that show less need for

resources but still demand it, three stars are the ones who present a lack of

resources compared to five star hotels, data is logical for there are great

differences in YM investment between the two categories. If the same analysis

was performed according to dependency or independency of the hotels studied,

no remarkable evidence would be found for they are independent variables that do

not influence the analysis results.



Another difficulty is linked to the lack of trained staff where the variable is

dependent of the hotel category, after the Pearson’s chi-square test of three

hotels, four and five star hotels it is seen that they find it difficult to recruit staff

trained on YM or even staff that has any knowledge of it.

Once exposed the most relevant results on the research, chapter five will discuss

the findings, limitations and possible lines of future research.

Chapter 5: Conclusions and Recommendations


CHAPTER 5

CONCLUSIONS AND RECOMMENDATIONS

5.1. Conclusions

This chapter presents the conclusions of the research based on the results that

the main findings draw from primary data. This paper attempts to see the overall

objective of determining the level of YM implementation and if three, four and five

star hotels have a Revenue Manager figure. The specific objectives that were

proposed were whether hotels made a correct YM application and thus obtained

an increase in economic and management benefits, and to know if the YM

philosophy or culture was incorporated into the company and identify the obstacles

faced by hotels in applying the YM process of as the research areas of the study.

Referring to the overall goal that was set previously, we conclude that the degree

of implementation of YM policies in three, four and five star hotels of the city of

Madrid is high, noting that a large number of the hotels that responded to the

survey, took at least 66 actions out of 77 proposals representing a 85.71%. This

fact is mainly influenced by the independence of the hotel or by belonging to a

hotel chain management, the latter representing 78.9% of the effective sample

against 21.1% of independent hotels, hotel chains have greater degree of

implementation than independent hotels engaged in YM but not at the level of the

hotel chains. Moreover, hotels are fully supported in the development of the YM

strategies by management or hotel property in 100% of the cases, and recognized

that a 90.91% of the RM team had received specific training and are informed

daily about the evolution of YM through forums, blogs, conferences, etc. Thus

demonstrating that the culture or philosophy is incorporated in business

management.



However only 56.5% of the hotels surveyed have a Revenue Manager figure, on

the other hand, we must mention that many hotels belonging to chains do not

Revenue Manager figure in the hotel but work in central offices and operate

several hotels, data collected after the telephone interviews. Therefore the degree

of implementation of the Revenue Manager, recognized as the sole responsible for

managing YM, is in the process of integration into the hotels in the city of Madrid.

As for the specific objectives, it aims to show, if the correct application of YM

increases the economic and management benefits of the company, as well as the

obstacles encountered in their implementation. Referring to whether it increases

profits through proper information management, 93.4% of respondents agree that

the YM model maximizes information management. Information Management is

collected through the analysis of the YM department, which accounted for more

than four market segments in a 88.31% that influence the pricing in a way that

they offer different prices to different niche markets, where the hotel obtains profit

maximization. 72.4% hotels in Madrid apply market segmentation. When it comes

to analysis of the competition they often forecast short-term not at long-term, nor

they have tools for analysis of competition as bench and shoppers. 100% of the

hotels find Internet very profitable as it is becoming more common to self-manage

their own website which also serves as a marketing tool having their own built-in

CRS for on-line payments. Consequently they perform selection analysis and

positioning in the most profitable Internet channels they consider are distributing

their product in 91.95% of cases.

In recent years, hotels have incorporated Crosselling and Upselling in their

management techniques and a 81.80% recognizer it as a source of extra income

where they generate an increase in profit.

In terms of increasing economic benefits, a responsible conclusion cannot be

made, since the figures provided were insufficient to make a credible claim, due to

the reduced response rate that was very low or almost non-existent.



As the main obstacles faced by managers in YM implementation, data suggest

that 71.6% of the hotels "do not perceive as fair price variations" compared to

28.4% who "do perceive price changes as fair". After a review of the literature,

there is research to partially support the results of this research. According to

Jones (2000, in Talón, 2009) the implementation of YM improves business

performance from three perspectives:

• Increased knowledge about the client: the mode of action and perception of

value product or service.

• Optimizes information management, enabling increased efficiency in

handling data and creating estimates of demand, allowing prices to adjust.

• Provides the effects of changes in reserves.

After analyzing the responses, I find myself in a position to strengthen with data

Jones first two statements, the incorporation YM actions allow hotels to "Select

better customers" and therefore implement a process that "optimizes information

management”. In the results analyzed it is seen that hotels have high number of

actions obtaining a broad vision of the market and enabling them to profit from

improving the profitability of economic and management benefits.

The lack of specific software applications and the lack of trained personnel in this

discipline is found as a major obstacle to achieve profitability in their management,

also state that they have not yet implemented integral YM and actions are

commonly performed towards rooms.

5.2. Limitations First limitation is considered to be the theoretical sample size of 160 hotels, where

there was a response rate of 81 hotels that represents a 50.63%. Despite not

being very representative and that the total of the effective sample is half of the

theoretical sample of departure which are160 hotels.



The four star hotels group is over represented with respect to others, where five

star hotels represent a small sample compared with the number of hotels in three

or four star. This limitation was resolved at the time of the effective sample weight,

but even so the study results it cannot be extrapolated to other cities, a fact to take

into account.

The data collection period of our study occurred in June 2009, in an advanced

stage of the global economic crisis, therefore the quarterly balance sheet data,

and occupation data are not the same as in times of normal economic situation.

Economic benefits are reduced in many cases, and they do not invest in

equipment or training, so this circumstantial event has altered this point.

5.3. Recommendations for further research

This section discusses some ideas that have emerged during the review of the

literature and issues that appeared during the investigation. I give some

recommendations for future research, which aims to:

• The creation of a best practices manual regarding YM management: based

on the literature, consultations with experts and data collected in research,

it would be interesting to conduct a good practices manual that serves to

optimize YM management in hotels.

• Conduct a study on the job skills of a Revenue Manager, since Spain has

no information of the functions it effectively performs and the abilities

needed. This will help HH.RR. Departments when looking to recruit

Revenue Managers.

• Longitudinal studies: It would be good for better knowledge and control of

YM management in the city of Madrid, make continuous studies to measure

sporadic over time the implementation degree varies, and which aspects of

YM management have been modified or reinforced.

• Study the impact generated by the Upselling and Crosselling trainings in

reservations and front desk staff.

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Appendix


APPENDIX

Appendix A: Delphi 85

Appendix B: Questionnaire 98

Appendix C: Presentation Letter 104

Appendix D: Briefing 105

Appendix A: Delphi

85

SURVEY INTERVIEWER:

DATE:

RESPONDENT:

Dear Mr. / Mrs.:

After analyzing the results from the first phase in the Delphi analysis related with the

usage of Yield & Revenue Management (RM) in Hotels in Madrid (Spain), in which you

collaborated in October-November 2008, we send you the main results and request your

cooperation in this second phase.

Consequently, we ask you to reconsider your answers taking into account the average of

all respondents. In order to make it we reattach the survey divided into four columns: in

the first column you will find your previous answers; in the second column the average of

all respondents; in the third one the standard deviation; and in the last one you have the

opportunity to re-asses your previous answers.

We have introduced new variables suggested by the different experts participating in the

Delphi and we need you to value them between 0 (not relevant) and 4 (very important)

based on the importance of its application for correct implementation of RM. The purpose

is to discriminate between different variables so it is very important to value each variable

in the weight the expert considers appropriate.

In the last part of the questionnaire, the ranking for the different sections - RM culture;

demand forecast; competitive benchmarking; segmentation; budgeting; pricing strategy;

calculate and update booking limits, sales and evaluation - is presented. Taking into

consideration your previous answer and the most voted ranking for each section from all

respondents, we ask you to reconsider your previous ranking Once again, and taking into

consideration your previous answer and the average of all respondents, we ask you to

reconsider your answer. As several experts have suggested, we have included an

additional section "Distribution channels’ analysis”. We would like to have your opinion

about this inclusion and its ranking in relation with the other eight sections, previously

included.

We thank you again for your invaluable cooperation.

Yours sincerely,

Pilar Talón Ballestero,

Universidad Rey Juan Carlos (Madrid-Spain)

Appendix A: Delphi

86

A. PARAMETERS THAT ESTABLISH THE CORRECT PRACTICE AND

IMPLEMENTATION OF RM

Value between 0 (not relevant) to 4 (very important) the importance of these

parameters in the correct definition of RM implementation in a hotel.

1. RM CULTURE YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. Management and property support the development of RM

strategies.

2. The existence of the Revenue Manager figure with exclusive

competences.

3. The existence of a Revenue Management Team.

4. The Revenue Management Team has, at least, one meeting

per week

5. Implementation of Revenue Management Software (RMS).

6. Excel tables are used to manage RM.

7. Property Management System (PMS) and RMS are connected.

8. Staff trained internally for RM implementation.

9. Staff trained externally for RM implementation.

10. Staff in reservation and reception departments has incentive

programs.

11. RM is implemented in every department in the hotel

12. Reception staff is daily informed about results and forecasts.

Comments: ---------------------------------------------------------------------------------

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New variables suggested by experts: Value between 0 (not relevant) to 4 (very

important) the importance of these parameters in the correct definition of RM

implementation in a hotel.

1. RM CULTURE

0 1 2 3 4

13. Business Intelligence systems

14. To be updated in relation with RM and Marketing trends through blogs, newsletters,

forums, etc.

15. Connectivity between the Central Reservation System (CRS) and the Property

Management System (PMS).

Appendix A: Delphi

87

16. Give information to the client about dynamic prices.

17. Enough resources for the development of RM

18. Inter-relationships between the RM department and the Marketing and Sales De-partments.

Comments: -----------------------------------------------------------------------------------------

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2. FORECAST YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. RM department executes the forecasts

2. Monthly forecasts are done weekly

3. Quarterly forecasts are done every other week.

4. Annual forecasts are done monthly

5. The historical data (2 previous years) is used to make the

forecasts.

6. The historical data (previous year) is used to make the fore-

casts

7. Historical data available: number of clients

8. Historical data available: clients segmentation

9. Historical data available: sold rooms

10. Historical data available: occupancy rate

11. Historical data available: denied rooms

12. Historical data available: declined rooms

13. Historical data available: no-shows

14. Historical data available: understays

15. Historical data available: overstays

16. Historical data available: walk-ins

17. Historical data available: ARR

18. Historical data available: Revenue per Available Room

(RevPar)

19. Historical data available: GoPar

20. Historical data available: length stay

21. Historical data available: MPI

22. Historical data available: strategy followed in previous years

23. Historical data available: clients that have visited the hotel

more than once.

24. For forecasts present evolutions in bookings are compared

with past evolutions

Appendix A: Delphi

88

25. The type of market segment that makes each reservation is

known in advance.

26. Forecasts are done over sales in each department

27. Key accounts per segment

28. Conversion rate in each group.

29. Advance rate in confirming each group.

30. Total expense per group.

31. Group size

32. Turn downs and groups cancelations

33. Forecast OTB is under concern.

34. Pick up is analyzed on a daily basis.

35. Pick up is analyzed on a weekly basis.

36. Pick up per reserved room is analyzed.

37. Pick up per market segment is analyzed

38. External factors are analyzed

39. Future events are analyzed

Comments: -----------------------------------------------------------------------------------------

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2. FORECAST

0 1 2 3 4

40. Clients’ cancellation motives are recorded.

41. Future trends are taken into account.

42. Business Plan is taken into account.

43. Previous Forecasting Behaviour Models are analysed

44. Price sensitivity is analyzed in the different market segments.

45. Average stay is taken into account.

Comments: -----------------------------------------------------------------------------------------

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Appendix A: Delphi

89

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3. COMPETENCE COMPARATIVE ANALYSIS YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. Competence is identified.

2. Hotel positioning is determined at the long run.

3. Hotel positioning is determined at the short run.

4. Hotel positioning in search engines in Internet is determined.

5. Hotel positioning at distribution channels is determined.

6. Competition positioning in Internet is evaluated (Ex: ALEXA).

7. Location, prices and commercialization prices of the compe-

tency are evaluated.

8. Competency products and services are evaluated.

9. Competency pricing strategies are evaluated.

10. Competition strategies in distribution channels are evaluated.

11. The hotel uses electronic tools to evaluate competency prices:

Channel Managers and Shoppers, (Ex. Rate Shopping, The

Bench; Traveljungle).

12. The hotel measures the MPI

13. The hotel measures the “Average Rate Index” (ARI)

14. The hotel measures the “Revenue Generation Index”

15. The competencies strategies are analyzed in order to imple-

ment the most appropriate ones

Comments: -----------------------------------------------------------------------------------------

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Appendix A: Delphi

90




3. COMPETENCE COMPARATIVE ANALYSIS

0 1 2 3 4

16. Competence opinions are analyzed through the usage of Social Technolo-

gies.

17. In hotel chains hotel’s, the competence analysis is individual in each hotel

18. Competency is analyzed periodically.

19. Relationship between RM and economic statistics...

20. Property and Hotel Chain investment decisions

21. Government strategic decisions.

Comments: --------------------------------------------------------------------------------------

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Comments: --------------------------------------------------------------------------------------

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4.MARKET SEGMENTATION YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. The hotel differentiates more that 4 market segments.

2. Typologies of each market segments are analyzed

3. Origin of segments is analyzed

4. Market segments consuming behaviour is analyzed

5. Contribution of each segment to the final benefit is analyzed

6. The segments of the distribution channels.

7. Client’s satisfaction with RM strategies is analyzed.

Appendix A: Delphi

91




4. MARKET SEGMENTATION

0 1 2 3 4

8. Market segmentation based on price sensitivity.

Comments: --------------------------------------------------------------------------------------

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Comments: --------------------------------------------------------------------------------------

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5. BUDGET

0 1 2 3 4

4. Periodical comparison between forecast and budget.

5. Budget is done for each room.

6. Each department has its own budget

Comments: --------------------------------------------------------------------------------------

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5. BUDGET YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. Budget is based on the demand forecast of the RM department

2. Budget checked periodically

3. Budget based on different market segments

Appendix A: Delphi

92

6. PRICING STRATEGIES

YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. The fixing prices responsible are the commercial and RM de-

partments.

2. Different types of prices are used

3. Different types of tariffs are applied to different types of mar-

ket segments

4. In the lowest prices or tariffs restrictive criteria are applied

5. Dynamic packaging applied in the hotel.

6. Packages conformed by rooms and other services in the hotel

are created for tariffs differentiation.

7. Prices are uploaded to the different distribution channels with

more than 12 months in advance

8. Prices are uploaded to the different distribution channels 12

months in advance

9. Prices are uploaded to the different distribution channels 6

months in advance

10. Prices fixation are based on costs, demand and competency

11. Each market segment has its own discount structure

12. Tariff application is based on each market segment evolution.

13. Tariffs are variable in touroperator contracts and companies

contracts

14. ”Best Available Rate” strategy is applied

15. All distribution channels have price parity

16. The hotel does not sell cheaper than their negotiated accounts

17. RevPar per room and stay online information

18. Last minute tariff defined

19. Information available about the highest and lowest tariff ap-

plied

20. For certain promotion the client must fulfil certain requirements

21. Tariff revision based on cyclical fluctuations

22. Tariff revision based on local events

Comments: --------------------------------------------------------------------------------------

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Appendix A: Delphi

93




6. PRICING STRATEGIES

0 1 2 3 4

23. RM department decisions related with price prevail over Commercial De-

partment decisions.

24. Opaque tariffs are offered.

25. “Last Available Room” (LAR) conditions as added value over Negotiated

accounts over price.

26. Overbooking strategy taken into account.

Comments: --------------------------------------------------------------------------------------

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7. CALCULATE AND UPDATE BOOKING LIMITS AND SALES YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. Available rooms information available online.

2. Reservations can be rejected even when there are rooms

available

3. Upselling strategies applied

4. Crosselling strategies applied

5. Overbooking strategies applied

6. Reservations are accepted or rejected based on: the period

when there are made

7. Reservations are accepted or rejected based on: stay length

8. Reservations are accepted or rejected based on: season

9. Reservations are accepted or rejected based on: client

10. Reservations are accepted or rejected based on: services de-

manded

11. Reservations are accepted or rejected based on: payment type

12. Reservations are accepted or rejected based on: fidelity origi-

nated

13. Reservations are accepted or rejected based on: reservation

volume

14. Reservations are accepted when the income generated is

Appendix A: Delphi

94

higher than the possible income an extra room would make.

15. Reservations are accepted when the benefit generated is

higher than the possible income an extra room would make.

16. Tariff are closed or opened based on demand forecasts

17. Through channel manager tools tariffs can be updated online

in every distribution channel

18. Best Available Rate in hotel web site

Comments: ----------------------------------------------------------------------------------------

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7. CALCULATE AND UPDATE BOOKING LIMITS AND SALES

0 1 2 3 4

19. Group bookings are accepted or denied depending on the services requested.

20. Room auctions are used.

Comments: --------------------------------------------------------------------------------------

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Appendix A: Delphi

95

8. EVALUATION YOUR

ASSESMENT

EXPERTS

AVERAGE

STANDARD

DEVIATION

NEW

ASSESMENT

1. Benefits generated by RM application are analyzed through

different variables: occupancy, average daily rate; RevPar,

etc.

2. Results are revised daily

3. Results are compared with budget

4. Diversion analysis

5. Income and cost are analyzed based on market segment and

hotel departments

6. Staff is incentive to apply Upselling y Crosselling

Comments: --------------------------------------------------------------------------------------

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8. EVALUATION

7. 0 1 2 3 4

8. Decisions made in the last meeting are evaluated.

9. Competence indicators evaluated

10. Real prices take into account inflation.

Comments: --------------------------------------------------------------------------------------

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Appendix A: Delphi

96

B. SECTIOS RANKING

Taking into consideration your previous answer and the most voted ranking for each

section from all respondents, we ask you to reconsider your previous ranking. We ask

to assess the importance of each section between 1 and 8, giving 1 to the less

important section and successively until the most important section that would

have an 8.

YM PROCESS

YOUR ASSESMENT EXPERTS AVERAGE NEW ASSESMENT

RM Culture

Forecast

Competence Analysis

Segmentation

Budget

Pricing

Calculate and update

booking limits and

sales.

Evaluation

Comments: --------------------------------------------------------------------------------------

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Appendix A: Delphi

97

As several experts have suggested, we have included an additional section "Distribution

channels’ analysis”. We would like to have your opinion about this inclusion and its

ranking in relation with the other eight sections, previously included. We ask to assess

the importance of each section between 1 and 9, giving 1 to the less important

section and successively until the most important section that would have a 9.

YM PROCESS

1

2

3

4

5

6

7

8

9

RM Culture

Forecast

Competence Analysis

Segmentation

Budget

Pricing

Calculate and update

booking limits and

sales.

Evaluation

Channels Distribution

Analysis

Appendix B: Questionnaire

98

Survey on the Level of Yield Management

Implementation in three, four and five stars

hotel of the City of Madrid (Spain).

The questionnaire should be completed by the Revenue Manager or Hotel Manager, or any other

person who has detailed information on Yield Management strategies within the hotel. Please

provide us with the following contact data for consultations, clarifications or modifications on this

questionnaire make it necessary. If you have any questions about the terms used, please consult

the glossary included at the end of the questionnaire. You can also contact the coordinator of this

research at e-mail [email protected]

Hotel name:

Mr./Mrs.:

Position in the hotel:

City:

E-mail:

Telephone:

C1: Do you apply Yield or Revenue Managment in your hotel or hotel chain? Yes No

C2: ¿Since when? (indicate year):

P1. Hotel category: Three stars

Four stars

Five stars

P2: Size of Hotel: Number of rooms

Hotel capacity

P3. Management Model

Ownership

Rented Franchising

Management

Others:

P4. ¿Is it an independent hotel or does it belong to a hotel

chain?

Independent (pasar a P6) Belongs to a hotel chain (pasar a P5)

P5: IS YM tasks totally carried out in central headquarters,

totally in the hotel or both?

Totally at headquarters

Totally in the hotel Both

P6. ¿Who is the person responsible for YM in your hotel?

Manager Room Manager

Sales Manager

Reservations Manager Front desk staff

Hotel’s Revenue Manager

Others:


99

YM CULTURE AND RESOURCES

Point from 1 to 5 the impact of YM in the following aspects (where 1= highly disagree and 5=

highly agree) 1 2 3 4 5

P8.- ¿Do you believe housing department,sales and Management staff have knowledge on and

share YM goals?

P9.- ¿Do you relieve front desk and reservations staff properly justicies price variations to guests?

P10.- ¿Do you relieve guests percieve price variations are fair?

Following you will find several questions concerning YM in your hotel, please answer YES or NO:

YES NO

YIELD MANAGEMENT CULTURE AND RESOURCES

19. Have you been or are you being supported by hotel manager and /or hotel property or chain when developing YM strategies?

20. Is the RM team updated on YM issues through forums, blogs, newsletters, etc.?

21. Has the RM team received any training onYM?

FORECAST

22. Historical data are taken into account:

4.1. Types of Customer

4.2. Rooms sold

4.3. Average occupancy

4.4. Hotel’s room denials

4.5. No show reservations

4.6. Walk in rooms

4.7. Average room price or ADR

4.8. RevPar

4.9. GovPar

4.10.Lenght of stay

4.11.Segmented key accounts

4.12.Conversion ratio of groups

YIELD MANAGEMENT RESOURCES RESOURCES YES NO Denomination (software) Year of Purchase

P11.- Does the hotel have any special

computer application software for YM?

P12.- Do you use Excel spreadsheets to

perform YM tasks?

P13.- In case of having a responsable for

YM tasks. Is the dedication full or part

time?


100

4.13.Group denials, Group cancellations

23. Forecast compares the development of existing reservations with the evolution in the past

24. Estimation takes into account the rooms booked at present (OTB)

25. It is known with what advance the different segments book

26. Pick up is analyzed:

8.1. Daily

8.2. Weekly

8.3. Per total rooms

27. Enviromental factors are analyzed

28. Future events are analyzed

29. It takes into account future enviromental trends

COMPETITIVE ANALYSIS

30. It identifies competition

31. It determines the positioning of the hotel:

13.1. long-term (more than 12 months)

13.2. short-term (less than 12 months)

13.3. With regard to competition in search engines

13.4. With respect to its competition in distribution channels

14. It Analyzes :

14.1. Competitive advantages (location, price, marketing strategies) in competition with regard to your hotel

14.2. Pricing strategies of competition

14.3. The distribution channels strategies of competition

15. Tools are used to analyze the pricing strategies of competitors: Shoppers (Ej.Rate Shopping, etc..), The Bench, comparators (eg Traveljungle), etc.

16. It measures:

16.1. MPI

16.2. ARI

16.3. IRG

17. The Analysis on competition is periodic

DEMAND SEGMENTATION

18. Regarding segments, there are at least 4 market segments.

19. It Analyzes:

19.1. the types of segments

19.2. the origen of segments

19.3. Buying behaviour of each segment


101

19.4. The contribution of each segment to profit

19.5. Segments that come through distribution channels

BUDGETING

YES NO

20. Is performed taking into account RM Departments demand forecast

21. The Budget is done by market segments

PRICING

22. The Sales and Revenue Management Departments are responsible for setting prices

23. Differentiated prices are used

24. Several different rates are used depending on different market segments

25. The lowest rates have restrictive criteria or barriers to their implementation

26. “Packaged” prices are provided (room with other services)

27. Room differentiation is done by adding attributes that do not pose a significant cost increase

28. Prices are fixed taking into account the costs, demand, competition and distribution channels

29. In Tour operador contracts and corporate business accounts rates can vary

30. BAR model is used "Best Avaible Rate"

31. There is equality of prices offered by the vendor in all distribution channels

32. Information of higher / lower rate applied is available

33. To apply promotions predetermined requirements are necessary

34. When reviewing rates the influence of local events are taken into account

DISTRIBUTION CHANNELS

35. The positioning of the various distribution channels are analyzed

36. The most profitable channels are selected

37. Online reservations can be done from the hotel’s website

UPDATING LIMITS OF RESERVATIONS AND SALES

38. Available Updated information on the number of rooms available

39. Upselling and Crosselling techniques are applied in sales

40. Over capacity reservations are made (overbooking)

41. Reservations are accepted or denied in terms of:

41.1. Lenght of stay

41.2. Season

41.3. Volume of reservations

42. Reservations are always accepted when producing more benefit than the profit of having an extra room avail-able

43. Rates are opened or closed depending on the demand forecasts

44. You can change rates at all "channels" (channel management)

45. Lower rates cannot be found on other sites other than the hotel’s site


102

EVALUATION

46. Benefits resulting from the application of YM are assessed taking into account several variables: employment, price, RevPAR, etc.

47. Results are reviewed daily

48. It compares the actual with the budgeted

49. Deviations are analyzed

50. Reservations and front desk staff are encouraged with incentive schemes when applying Upselling and Crosselling techniques.

ECONOMIC DATA

Profitability Data Real Datal: % Approximate% of variation between

the year prior to the implementation of YM and the

two subsequent years

Ocupamcy

Average Rate

Average Income per room (RevPar)

Gross Operating Profit (GOP) = Operating Incones – Operating Expenses)

Profitability Data Perception: What % of previous estimates

variations are attributable to the implementation of

YM in the hotel?

Ocupancy

Average Rate

Average Income per Room (RevPar)

Gross Operating Profit (GOP) =(Operating Incomes – Operating Expenses)

BENEFITS

Value from 1 to 5 the impact of YM in the following aspects (where 1= non influential and 5= fully influential)

1 2 3 4 5

1. Increases Hotel’s benefit

2. Increases knowledge on the market and my product

3. I obtain better results that my competition

4. It optimizes information management

5. Better manage my relationships with intermediaries

6. It allows me to select the best customers

7. Allows greater flexibility of the workforce

8. Improves the hotel’s image

9. Increases staff motivation

10. Increases decision making speed


103

DIFFICULTIES AND OBSTACLES Value from 1 to 5 (where 1= non influential and 5= fully influential) should these situations take place in your hotel

1 2 3 4 5

1. Lack of staff understanding regarding YM goals

2. Lack of resources

3. Lack of trained staff

4. Lack of interconnectivity of systems

5. Lack of integral YM throughout the hotel

6. Shortage of computer applications

7. Lack of Historic Data

8. Customer lack of understanding

9. Distributors and trade’s lack of

10. Others:

GLOSSAR

RMS: Revenue Management Software. PMS: Property Management System. CRS: Central Reservation System. RevPar: Income per Room Available. GopPar: Profit per Room Available. ADR: Daily Average Ratio. ARI: Average Rate Index. IGR: Revenue Generation Index. MPI: Market Penetration Index. Pick up: Pick up: are the reservations we expect to receive, based on our experience and analysis.

Adding them to the reservations we have today (OTB), we can start making our forecast.

Appendix C: Presentation Letter

104

A/A: Hotel Name Hotel Manager Address - Location

Dear Mr/Ms., The University Rey Juan Carlos of Madrid together with the University of Applied Sciences FH Krems in Austria, through a collaboration agreement are conducting a survey on the degree of implementation of Yield Management in three,four and five star hotels of the city of Madird (Spain). This is an inquiry led by Professor Pilar Ballesteros Talón Department of Applied Economics at the School of Tourism at the Universidad Rey Juan Carlos. From the conviction of the protagonist character of tourism in the present and future, we intend to create a framework on the degree of implementation of the Management of Yield Management in the city hotels. This project aims to determine the strategies adopted by Hotels in Madrid to meet current industry challenges and the need to increase the economic benefits and management of hotels. For the success of this research it is essential the collaboration of managers and / or Yield Management Managers of the 160 hotels selected, by completing the questionnaire. The treatment of the information collected will be totally confidential and data will be analyzed in aggregate, so that no company can be identified by their results. The questionnaire will be send to you via e-mail where we direct you to the same email address [email protected], The questionnaire is quick to respond and if you have any question you would like to ask, do not hesitate to contact us, we will be glad to help you. In appreciation for your collaboration, once finished the research if you wish to, you will receive the report, which we believe will be of great interest, insisting that all answers are protected by existing legislation on data protection and statistical confidentiality (Governing Law 12/89 statistical confidentiality), and in no case will reveal the source or publish results that can be identified. I remain at your disposal for any additional information you may want on this issue and take this opportunity to send my best regards. Raúl Mateo Lapuente Inquiry Coordinator

Contact:

Raúl Mateo Lapuente

Tfno. 606322302 E-mail: [email protected]

Appendix D: Briefing

105

BRIEFING NOTES FOR THE HOTEL SURVEY

Name of research: Study on the degree of implementation of yield management

in hotels of three, four and five star in the city of Madrid.

Goal: To determine the degree of implementation of yield management in three,

four and five star hotels of Madrid. It aims to demonstrate that the correct

application of Yield Management increases corporate profits, both financial and

management and to know there major obstacles for its implementation.

The survey does not have commercial purposes, anonymity is fully guaranteed

and respondents may receive, upon request, a copy of the report.

It samples 81 randomly selected hotels. First contact via mail with telephone

follow-up.

The survey must be completed, preferably by the Revenue or hotel Manager. If it

fails to respond, we will be contact with the person performing these tasks, in such

cases it should be noted appropriately in the corresponding questions on the first

page (Identification of the person answering the questionnaire).

At the present stage we are proceeding to close of fieldwork, collecting the

pending questionnaires by mail. En la etapa actual estamos procediendo al cierre

del trabajo de campo recogiendo aquellos cuestionarios que han quedado

pendientes por vía postal. The selected companies have not refused to be

interviewed but are consistently delayed in forwarding their answers via mail.

PROTOCOL FOR THE QUESTIONNAIRE AND COLLECTION AND CONTACT. Initial call: Presentation to front desk: "My name is XXX, we are calling from URJC

in relation to a research study that is carried out on the implementation of yield

management in three, four and five star hotels of. I’m calling to complete a

Appendix D: Briefing

106

questionnaire we sent through the Association of Hoteliers Madrid a few weeks

ago. May I speak with the person in charge of Yield Management? "('Person to

Contact' - best question the person responsible for the YM tasks in the hotel, who

will in some cases the figure as Revenue, Manager, Front Desk Manager, Sales

Manager, etc.,)

To the contact person: "Good morning / afternoon, my name is XXX and I’m will

calling from URJC. The call is related to the questionnaire that we sent through the

regional federation of hoteliers. Could I know if you received and completed it or

on the other hand could we complete it now? “

If YES: "Have you already sent it?" (Yes, "finish call, and thank them).

If NOT: "Would you mind if we take a few minutes to fill it in now?" (YES

questionnaire/No- what other time could I call you back to complete it?

Completion of the interview: Once collected the questionnaire, thank their

attention and participation, also remember that "maybe" make contact with the

interviewee to confirm that the interview has been done effectively.

empirical findings in three,four and five stars hotels in the city of madrid

Documents

master thesis

great thanks

price management

special thanks

yield management strategies

rector of imc

city of madrid spain

business ma thesis coach