Masaryk University

Faculty of Economics and Administration Field of study: Business Administration

THE APPLICATION OF PROSPECT

THEORY IN MARKETING

Diploma Thesis

Thesis Supervisor: Author:

Ing. Jaromír SKORKOVSKÝ, CSc. Zuzana GOCMANOVÁ

Brno, 2012

Masarykova univerzita

Ekonomicko-správní fakulta

Katedra podnikového hospodářství

Akademický rok 2010/2011

ZADÁNÍ DIPLOMOVÉ PRÁCE

Pro: GOCMANOVÁ Zuzana

Obor: Podnikové hospodářství

Název tématu: VYUŽITÍ PROSPEKTOVÉ TEORIE V MARKETINGU

The Application of Prospect Theory in Marketing

Zásady pro vypracování

Cíl práce:

Cílem této práce je navrhnout využití prospektové teorie v marketingu a rozhodovacích

procesech. Autorka v práci popíše prospektovou teorii a bude specifikovat hlavní oblasti

jejího použití. Budou specifikovány důvody používání této teorie, podmínky potřebné pro její

aplikaci a množinu omezení, která jsou s využíváním prospektové teorie spojena. Autorka

navrhne využití této teorie v marketingové strategii konkrétního podniku.

Postup práce:

V teoretické části budou popsány základy prospektové teorie. Budou specifikovány procesy,

kde se mohou realizovat přínosy jejího využívání a případná omezení, které jsou s

využíváním prospektové teorie spojeny. V praktické časti bude provedena studie vybraného

podniku (podniků), ve které budou popsány procesy spojené s marketingem a budou

specifikovány možnosti využití prospektové teorie, důvody jejího využití a přínosy očekávané

a případně realizované. Budou konstruovány důkazy týkající se ekonomického opodstatnění

využití prospektové teorie.

Použité metody:

Studium odborné literatury týkající se problematiky prospektové teorie a důvodů využívání

této teorie a případně dalších relevantních nástrojů. Autorka bude využívat standardní metody

používané při konstrukci prací tohoto charakteru jako je pozorování a popis, osobní interview

a dotazníky, měření, srovnávání, analýza a syntéza a to tak, aby tyto metody vedly k řešení,

tedy posouzení konkrétních přínosů využívání prospektové teorie.

Rozsah grafických prací: (Předpoklad cca 10 tabulek a grafů)

Rozsah práce bez příloh: 60 – 70 stran

Seznam odborné literatury:

Choices, values, and frames. Edited by Daniel Kahneman - Amos Tversky.

Cambridge, UK: Cambridge University Press, 2000. xx, 840 s. ISBN 0-521-62749-4.

Judgment under uncertainty: heuristics and biases. Edited by Daniel Kahneman -

Amos Tversky - Paul Slovic. 1st ed. Cambridge : University Press, 1982. xiii, 555.

ISBN 0-521-28414-7.

LAKSHMAN, Krishnamurthi - TRIDIB, Mazumdar. Asymmetric Response to Price

in Consumer Brand Choice and Purchase Quantity Decisions. The Journal of

Consumer Research, 9, 1992, 3/1992, od s. 387-400, 13 s. 1992.

ROBERT, Meyer - ERIC J., Johnson. Empirical Generalizations in the Modeling of

Consumer Choice. Marketing Science, INFORMS, 14/1995, 3/1995, od s. 180-189,

9 s. ISSN 0732-2399. 1995.

YUPING, Liu. Prospect Theory: Developments and Applications in Marketing.:

Department of Marketing, Rutgers University, USA, 1998.

Vedoucí diplomové práce: Ing. Jaromír Skorkovský, CSc.

Datum zadání diplomové práce: 4. 3. 2011

Termín odevzdání diplomové práce a vložení do IS je uveden v platném harmonogramu

akademického roku.

…………………………………… …………………………………………

vedoucí katedry děkan

V Brně dne 4. 3. 2011

Name and surname of author : Zuzana Gocmanová

Title of the diploma thesis : The application of prospect theory in marketing

Academic Department : Business Administration

Thesis Supervisor: Ing. Jaromír Skorkovský, CSc.

Year of defence: 2012

Annotation

The presented thesis “The application of prospect theory in marketing” tests prospect theory

in conditions of certainty in a marketing strategy of a chosen company. The theoretical part of

the work focuses on the scientific background and knowledge regarding the main issues of the

decision making process, namely the expected utility theory and its main challenger, the

prospect theory. The practical part presents a detailed view on the current sales situation in the

chosen company and goes deeper in research of prospect theory principles applied to a choice

in riskless situations. Two surveys are conducted to state how preferences among offered

services change. Positive evidence for reference dependence and loss aversion is found. Based

on the results of the research a solution is proposed that can lead to desired improvement in

service merchantability, when implemented in company’s marketing strategy.

Keywords

Expected utility theory, Prospect theory, loss aversion, reference point, decision making

under certainty

Anotace

Předložená diplomová práce „Aplikace prospektové teorie v marketingu“ testuje

prospektovou teorii za podmínek jistoty v marketingové strategii vybraného podniku.

Teoretická část práce se věnuje vědeckému rámci a poznatkům týkajících se procesu

rozhodování, jmenovitě teorii očekávaného užitku a jejímu hlavnímu soupeři, prospektové

teorii. Praktická část představuje detailní pohled na současnou situaci prodeje ve vybraném

podniku a hlouběji se věnuje výzkumu principů prospektové teorie, aplikovaným do

rozhodování za jistoty. Jsou sestaveny dva průzkumy pro sledování změn preferencí mezi

nabízenými službami. Je prokázána závislost na referenčním bodě a averze ke ztrátě. Na

základě výsledků průzkumu je navrženo řešení, které po zavedení do marketingové strategie

podniku povede k požadovanému zlepšení v prodejnosti jeho služeb.

Klíčová slova

Teorie očekávaného užitku, prospektová teorie, averze vůči ztrátě, referenční bod,

rozhodování za podmínek jistoty

Declaration

Hereby I declare that I disposed the Diploma Thesis “Application of the prospect theory in

marketing” by myself under the supervision of Ing. Jaromír Skorkovský, CSc. and that I

stated all the used literary resources and other scientific sources according to legislation,

internal regulations of Masaryk University and internal management acts of Masaryk

University and the Faculty of Economics and Administration.

Nitra, 25th

April 2012 ...................................................

The student’s signature

Acknowledgment

I would like to express my gratitude to my supervisor, Ing. Jaromír Skorkovský, CSc. for his

help and direction in the form of comments and suggestions that significantly improved the

thesis. I am very grateful for the never-ending support and guidance he provided me with.

Appreciation is extended to PUXtravel travel agency for their respective efforts and assistance

in the information rendered. A special thanks goes to the PUXtravel customers and

individuals who participated in the marketing survey and made the accomplishment of the

research possible.

Table of contents

Introduction ...................................................................................................... 9

I Theoretical part ........................................................................................... 11

1 DECISION THEORY ......................................................................................... 11 1.1 Historical milestones in the decision theory ....................................................... 11

1.1.1 Since ancient times until approximately the first quarter of twentieth century .. 11

1.1.2 The 1930s – 1950s .............................................................................................. 12

1.1.3 The 1950s – 1970s .............................................................................................. 12

1.1.4 The 1970s – nowadays ........................................................................................ 12

1.2 Expected Utility Theory ....................................................................................... 13 1.2.1 Basic definitions ................................................................................................. 13

1.2.2 Homo Economicus .............................................................................................. 13

1.2.3 Utility function .................................................................................................... 14

1.2.4 The von Neumann-Morgenstern axioms ............................................................ 14

1.2.5 Attitudes towards risk ......................................................................................... 15

1.2.6 Limitations of EUT ............................................................................................. 17

2 PROSPECT THEORY ........................................................................................ 19 2.1 Prospect theory assumptions ............................................................................... 19

2.1.1 The Editing process ............................................................................................ 20

2.1.2 The evaluation process ........................................................................................ 24

2.2 Cumulative prospect theory ................................................................................ 27

2.3 Limitations of prospect theory ............................................................................ 28

3 DECISION MAKING UNDER CERTAINTY.............................................................. 29 3.1 Microeconomic foundations of consumer behaviour ........................................ 29

3.1.1 Basic definitions ................................................................................................. 29

3.1.2 Utility .................................................................................................................. 29

3.1.3 The indifference curves ...................................................................................... 30

3.2 Prospect theory in riskless choice ....................................................................... 31 3.2.1 Basic definitions ................................................................................................. 31

3.2.2 Reference dependence ........................................................................................ 32

3.2.3 Loss aversion ...................................................................................................... 32

3.2.4 Diminishing sensitivity ....................................................................................... 35

4 PROSPECT THEORY IN MARKETING .................................................................. 36

SUMMARY OF THE THEORETICAL PART ................................................................... 38

II Practical part ............................................................................................... 39

5 PROJECT GOALS & OBJECTIVES ..................................................................... 39 5.1 Research question ................................................................................................. 39

5.2 Objectives .............................................................................................................. 39

5.3 Hypotheses ............................................................................................................. 40

5.4 Research methodology ......................................................................................... 40

6 INTRODUCTION OF PUXTRAVEL ...................................................................... 41 6.1 History of the company ........................................................................................ 41

6.2 Vision, mission and principles of PUXtravel ..................................................... 41

6.3 Services .................................................................................................................. 42

6.4 Features and trends .............................................................................................. 42

6.5 Analysis of the current situation of service merchantability ............................ 44

7 EMPIRICAL SURVEY ....................................................................................... 46 7.1 Research approach ............................................................................................... 46

7.2 Survey Design ....................................................................................................... 48

7.3 Data ........................................................................................................................ 48

7.4 Survey results and analysis .................................................................................. 49 7.4.1 Question 1 ........................................................................................................... 49

7.4.2 Question 2 ........................................................................................................... 52

7.4.3 Question 3 ........................................................................................................... 55

7.4.4 Testing of Hypotheses ........................................................................................ 58

7.5 Recommendations for PUXtravel ....................................................................... 61

Conclusion .......................................................................................................... 62

References........................................................................................................... 63

List of tables ....................................................................................................... 71

List of figures ..................................................................................................... 71

List of graphs ..................................................................................................... 71

List of abbreviations .......................................................................................... 72

List of appendices .............................................................................................. 72

9

INTRODUCTION

Neoclassical theory postulates that preferences between two options are stable and set to

satisfy certain properties, e.g. utility maximization, invariance, dominance and transitivity.

Several experimental studies of individual behaviour have provided strong evidence against

these assumptions, which are used in most theoretical and applied economic models, and

rejected the implications of the utility-maximizing hypothesis (see, for example, Blundell et

al., 1993). These results have led to call for a new economic paradigm to displace

conventional neoclassical theory and to be able to better explain the decision making process.

Daniel Kahneman and Amos Tversky (1979) developed a descriptive model of risky choice

making invoking psychological effects, called prospect theory. For this work and its further

extension, cumulative prospect theory (Tversky and Kahneman, 1992), and more generally

for "having integrated insights from psychological research into economic science, especially

concerning human judgment and decision-making under uncertainty" (The Royal Swedish

Academy of Sciences, 2002), Daniel Kahneman was awarded the 2002 Nobel Memorial Prize

in Economics.

Prospect theory is increasingly used to explain deviations from the neoclassical model and

anomalies in decision making caused by the paradigm of rational agents. In the last three

decades elements of prospect theory have been applied to explain behaviour in a variety of

contexts, such as finance, insurance, economics, political science, and consumer choice.

Empirical support for prospect theory comes mainly from experiments using conditions of

risk and uncertainty (Diamond, 1988; Elliot and Archibald, 1989; Loewenstein, 1988; Paese,

1995; Tversky and Kahneman, 1981; van Schie and van der Pligt, 1995; Cochran, 2001;

Barberis, Huang and Santos, 1999; Abdellaoui, Bleichrodt and Kammoun, 2011).

It is important to know whether and to what extent the support of prospect theory assumptions

generalizes to certainty circumstances. Most surveys concentrate on the endowment effect and

the role of current assets or status quo as a reference point (Kahneman and Tversky, 1991;

List, 2004; Sewell, 2009).

The lack of research work on application of prospect theory in settings that involve riskless

choices motivates the present research. This thesis aims at exploring the potential of prospect

theory in marketing of a concrete company. The research question is formulated as follows:

Will the use of prospect theory in an offer affect customer’s choice? To be able to answer the

question, two objectives are set for the thesis. 1) To analyze service merchantability in a

concrete company and identify the possibilities of improvement, and 2) to propose an

application of prospect theory in marketing of the chosen company that will lead to the

desired improvement.

10

To achieve the objectives, the research is designed to explain the theory and then inference of

the theory is drawn to develop survey questions prompting the loss aversion behaviour of

respondents. Author develops, tests, and evaluates a suggestion for implementation of

prospect theory elements to a choice among offered services.

Appropriate research methods are used, mainly personal in-depth interview with manager

responsible for marketing of the company, a conduction of an empirical survey, using two

questionnaires with a multiple choice questions format, data collection, objective

measurements, statistical analysis in a statistical software STATISTICA 10, data and results

evaluation, analyses of service merchantability and its changes.

11

I Theoretical part

The theoretical part explains a decision making process. In the first part of this work an

analysis of value of risky prospects is presented. Here the author is going to pay attention to

the two most relevant decision theories – the widely used Expected Utility Theory and its

main competitor The Prospect Theory. In the second part this analysis is extended to choices

under certainty in trades and transactions. The author shows how the principles of the

prospect theory, defined under conditions of risk and uncertainty, can be applied to decision

making in riskless situations, i.e. the consumer choice. The structure of theoretical part is as

follows. In chapter one the relevant literature within economic models of decision theory is

briefly overviewed, with focus on the neoclassical model of expected utility theory. Chapter

two introduces the prospect theory principles, defined for risky situations. In chapter three the

models are adapted to conditions of certainty. The use of prospect theory in marketing is

described in chapter four.

1 DECISION THEORY

The decision making process is a part of one’s everyday life. It has been therefore studied by

many disciplines for decades, even centuries. The most significant results have been brought

by philosophy, mathematics, economics, psychology, sociology, even political science and

statistics, computer science – artificial intelligence studies – and so called marketing science

that focuses on the consumer choice (Skořepa, 2006a).

The search for decision making systems and decision criteria came to be known as decision

theory (Dowling and Yap, 2007). The starting point of decision making as a separate field of

study can be set to the year 1954. Within this field a relation between two analyses has been

studied: a normative analysis, concerned with the nature of rationality and the logic of

decision making (how preferences should be), and a descriptive analysis, concerned with

people’s beliefs actions (preferences as they are) (Kahneman and Tversky, 2000).

1.1 Historical milestones in the decision theory

All the decision making approaches can be divided into four major historical stages. They

differ by how the relationship between the norm (a decision considered to be the perfect one)

and the actual decision making was perceived.

1.1.1 Since ancient times until approximately the first quarter of twentieth century

The consensus was that the norm and the reality are the same and that people always make the

right decisions. The representatives of this approach were C. Huygens, B. Pascal and P. de

Fermat. The main objector in this period was Daniel Bernoulli who introduced the St.

Petersburg paradox (Bernoulli, 1738).

12

1.1.2 The 1930s – 1950s

The belief was that people make decisions according to the norm. Nevertheless, they happen

to occasionally make mistakes that can be easily explained.

Representatives of this period were mathematician John von Neumann (1903-1957) and

economist Oskar Morgenstern (1902-1977) who introduced the Expected Utility Theory and

decision making axioms. An objector was a French economist Maurice Allais who proved this

theory wrong in his experiment at an International conference on Risk in Paris, 1952 (Allais,

1953).

Another notable author in this area was a Nobel Prize winner Herbert Simon (1916-2001). He

claims that an individual makes unnormative decisions systematically. He suggests it is

because his limited abilities and the complexity of decision problems he is faced with (Simon,

1979).

1.1.3 The 1950s – 1970s

This is the most sceptic phase. The actual decision making was considered not to meet the

norm and thus perceived as not always logical, in the economic sense (Jones, 2007).

The collection of theories from this period is labelled Behavioural decision theory.

The best known and most significant example is the Prospect Theory (1979) proposed by

Daniel Kahneman (*1934) and Amos Tversky (1937-1996) (Kahneman and Tversky, 1974;

Kahneman and Tversky, 1986; Kahneman and Tversky, 1979).

1.1.4 The 1970s – nowadays

The decision making is proved to be unnormative and this is viewed as reasonable (Skořepa,

2006a). One of the representatives, a German psychologist Gerd Gigerenzer, sees the decision

making as imperfect, but still good adapted to the circumstances (Gigerenzen et al., 1989).

The decision theory focuses on explaining and predicting the individual decision behaviour.

Risky, uncertain, and riskless (certain) choices are commonly distinguished. The decision

under risk is making a choice among gambles that yield monetary outcomes with specified

and objective probabilities. In the decision under uncertainty the probabilities of possible

outcomes are not known to the decision maker (Skořepa, 2007b). Frank Knight’s

(1921; p.233) definition of risk: “to preserve the distinction... between the measurable

uncertainty and an immeasurable one we may use the term “risk” to designate the former and

the term “uncertainty” for the latter.” A riskless decision concerns a choice between options

where the outcomes (a service or a good) are known and certain (Kahneman and Tversky,

2000).

13

1.2 Expected Utility Theory

The Expected Utility Theory (further in the text referred to as EUT) is a neoclassical model of

choice first introduced by John von Neumann and Oskar Morgenstern (1944) in their book

Theory of Games and Economic Behaviour.1 It is considered the groundbreaking text for the

field of the Game Theory. EUT has been generally accepted as a normative model of rational

choice (Keeney and Raiffa, 1976) and widely applied as a descriptive model of economic

behaviour (e.g., Friedman and Savage, 1948; Arrow, 1971).

EUT analyses the choices among risky projects that yield outcomes with objective

probabilities. It represents the foundation stone upon which the decision making under risk

and uncertainty is built (Schotter, 2009).

1.2.1 Basic definitions

Let be a finite set of outcomes for action A. In the situations under risk

the action A is described by the objective and known probability vector ,

where (Jehle and Reny, 2001).

To each of the outcomes xi in A a probability pi is assigned, see table 1. Preferences between

simple lotteries with only two outcomes are considered.

Table 1: Probabilities of outcomes of action A

A x1 x2 ... xn

pA p1 p2 ... pn

Source: Author

1.2.2 Homo Economicus

Homo Economicus2 is a term used for the EUT decision maker.

He is seen as a rational

economic agent, who strives to obtain the highest possible utility from his choice of provided

alternatives. This individual always prefers the best possible option available. Reversal of

preferences is not allowed. With help of the axioms mentioned further in the text this model

describes a decision maker who can make consistent comparisons among alternatives (Jehle

and Reny, 2001).

1 The derivation of expected utility from its axioms appeared in an appendix to the Second Edition of this book

in 1947. 2 This is a specific terminology, The Oxford English Dictionary does not mention Homo economicus.

14

1.2.3 Utility function

The agent’s preferences are formulated by a binary relation, , defined on the set of

alternatives, A. If , we say that “x1 is at least as good as x2”, for this individual.

A real valued function is called a utility function representing the preference

relation, , if for all (Jehle and Reny, 2001).

For any rational agent, there exists a mathematical function u assigning to each outcome xi a

real number u(xi), while capturing the agent's preferences over gambles, such that the

individual perceives action A to be better than action B, if

3

- expected utility (denotes the expected value of u in A)

– utility function, it transforms the probabilities pi

– probability of outcome xi of action A

– probability of outcome xi of action B

– the possible outcomes

1.2.3.1 Utility maximization

The rational individual will always act in his self-interest. Hence, he will always choose the

action that maximizes his expected utility. Any agent trying to maximize the expected utility

will obey four von Neumann-Morgenstern axioms.

1.2.4 The von Neumann-Morgenstern axioms

Axioms are intended to give formal mathematical expression to aspects of decision making

behaviour and attitudes toward the alternatives (Jehle and Reny, 2001). There are four

axioms of the expected utility theory that define a rational decision maker. They are

completeness, transitivity, independence and continuity (von Neumann and Morgenstern,

1944).

1.2.4.1 Completeness

Completeness assumes that an individual has well defined preferences. For any two actions A

and B exactly the following holds:

, (either A is preferred, B is preferred, or there is no preference)

3 Adapted from Skořepa, 2006b.

15

1.2.4.2 Transitivity

Transitivity assumes that preference is consistent across any three outcomes:

If and , then (if x1 is preferred to x2 and x2 to x3, then

and , and so in order to maximize utility, a rational agent would prefer x1 to

x3).

1.2.4.3 Independence

If , then for any action C and holds:

1.2.4.4 Continuity

If , then there exists a unique probability , such that the agent is

indifferent between the lottery and the lottery B with certainty.

All economic models of rational choice include two more axioms:

1.2.4.5 Dominance

If A is at least as good as B in every respect and better than B in at least one respect, then A

should be preferred to B.

1.2.4.6 Invariance

Invariance requires that the preference order between actions should not depend on the

manner in which they are described. Two versions of a choice problem, equal when thrown

together, should elicit the same preference when shown separately (Kahneman and Tversky,

2000).

1.2.5 Attitudes towards risk

EUT combines linearity in probabilities and a utility function, which is either concave or

convex if a decision-maker is risk averse or seeking (Cochran, 2001).

Let cA be the certainty equivalent of action A. It is a sure amount of payoff that an individual

considers to be exactly as good as a given gamble. We say therefore that the individual is

indifferent between these options. The more risk averse a person is, the lower his or her cA

(Dowling and Yap, 2007).

16

1.2.5.1 Risk aversion

Risk aversion is a preference for a sure outcome over a gamble that has higher or equal

expectations. A risk-averse agent prefers to reduce uncertainty; hence, the certainty equivalent

is less than the expected value of the gamble: (Skořepa, 2006b).

The utility function of a risk-averse agent is concave – it increases quickly initially and then

flattens out. This implies that money is more valuable at the beginning than the additional

sums of money once the agent is rich (Shor, 2006).

Figure 1: Utility function of a risk averse agent

Source: Author after Shor, 2006

1.2.5.2 Risk seeking

Risk seeking is a rejection of a sure outcome in favour of a gamble of equal or lower

expectations. The certainty equivalent of a risk seeking agent is more than the expected value

of the gamble: . The utility function of a risk seeking agent is convex, see figure

2.

Figure 2: Utility function of a risk seeking agent

Source: Author after Shor, 2006

17

1.2.5.3 Risk neutrality

Risk neutrality represents indifference between a sure outcome and a gamble of equal

expectations. The certainty equivalent of a risk neutral agent equals the expected value of the

gamble: . The utility function for a risk neutral agent represents that every euro is

worth as much as every other.

Figure 3: Utility function of a risk neutral agent

Source: Author after Shor, 2006

1.2.6 Limitations of EUT

Even though the EUT is agreed to be the basic economic theory of choice, there exist

critiques of this neoclassical model. The first one appeared only a few years after the EUT

was first published. The first economist to draw attention to its shortcomings and

imperfections was Maurice Allais (1953). His observations were confirmed and expanded a

few years later (Skořepa, 2007a).

The criticism of EUT is focused mainly on the Homo Economicus concept, maximization of

the expected utility and the von Neumann-Morgenstern axioms.

1.2.6.1 The “Homo Economicus” criticism

Most people do not act as a rational agents (in the economical sense of rationality), but

instead make decisions based on simple rules that use limited information. According to EUT,

different ways of presenting the same information should lead to the same decision.

Nevertheless, the rationality assumptions of EUT have been questioned and have not found

empirical support (Slovic and Tversky, 1974). Research has proved that people's decision

making is heavily influenced by the framing of the problem (Diamond, 1988; Elliot and

Archibald, 1989; Loewenstein, 1988; Paese, 1995; Kahneman and Tversky, 1981; van Schie

and van der Pligt, 1995), which directly violates the assumption of a rational individual in

EUT.

18

1.2.6.2 The “Maximization of the expected utility” criticism

Research has shown that when outcomes are uncertain, individuals often follow courses of

action that do not maximize expected utility. Furthermore, maximization of the expected

utility fails to explain the existence of both insurance and lotteries (Basili, 1999). One

explanation bring Kahneman and Tversky (1982) who argue that the tendency for consumers

to simultaneously purchase insurance and lottery tickets is due to people overweighting small

probabilities – of both winning a lottery and events covered by insurance.

1.2.6.3 The “von Neumann-Morgenstern Axioms” criticism

As mentioned above, decision makers violate transitivity by reversing preferences as the

context changes. Moreover, decision problems can be described in multiple ways that lead to

inconsistent preferences, contrary to the invariance criterion of rational choice (Kahneman

and Tversky, 2000).

Allais (1953) was probably the first one to indicate this phenomenon at the International

Conference in Paris. He showed that this concerns not only ordinary people, but individuals

“very circumspect” and “considered to be very rational in general” (Allais, 1953; p. 527),

when he demonstrated his experiment on the participants of this conference. He concentrated

on two pairs of actions where in one of the pairs there is one action offering a sure outcome.

He managed to confirm his hypothesis that this certainty would lead to attractiveness of this

action over the other option, whereas such a choice is inconsistent with the EUT. Allais

presents two types of such a situation, later labelled as the common consequence effect and

the common ratio effect. They are known in decision theory as the primary departures from

expected utility (Skořepa, 2006b). Kahneman and Tversky (1979) as well as later Starmer

(1992) proved their existence with hypothetical outcomes in experiments. Cubitt, Starmer and

Sugden (1998) confirmed these effects also with real outcomes of actions.

Some of the examples used in experiments appear to be “decision illusions”, working on the

same principle as visual illusions. An individual cannot help being fooled by them, even when

pointed out and though knowing the basic probability and optical laws (Ariely, 2008).

MacCrimmon (1968) pointed out that some – not many – attendees of various experiments

that had violated transitivity by their choices refused to admit they had made a mistake.

Kahneman and Tversky explain that human mind will always lead to certain mistakes, even if

the individual have high education and is promised any amount of money for the normative

answer.

These investigations show that using expected utility as a descriptive tool often leads to

incorrect predictions of people's behaviour. Studies show that despite the EUT suggestions,

individuals can act irrationally when making a decision. Moreover, these irrational behaviours

are neither random nor senseless. They are systematic, and since people repeat them in the

same way, predictable (Ariely, 2008).

19

2 PROSPECT THEORY

Prospect theory (further in the text referred to as PT) is a behavioural economic theory that

describes judgement and decision making process between alternatives that involve risk. In

the original formulation the term prospect was used as a synonym for a lottery or gamble

(Kahneman and Tversky, 2000).

The theory was developed by psychologist Daniel Kahneman and cognitive and mathematical

psychologist Amos Tversky in 1979. For his work on this theory, Daniel Kahneman was

awarded the 2002 Nobel Memorial Prize in Economics.

PT represents the main challenger and critique of EUT as a descriptive model of decision

making under risk. It offers an alternative model to explain instances where the traditional

EUT failed to explain people’s choices (Tversky, 1969).

Prospect theory suggests that

(1) people evaluate a prospect based on gains, losses and neutral outcomes (such as

maintenance of status quo) rather than in terms of states of wealth

(2) people view gains and losses separately and differently

(3) the decision weight people put on an outcome is a nonlinear function of the probability

PT introduced a couple of traits that are able to give an explanation to some effects in

economics considered as anomalies. The main tenets of PT are the following three: The

concept of reference dependence, loss aversion and transformation of probabilities.

2.1 Prospect theory assumptions

According to prospect theory, the decision process can be deconstructed into two distinct

phases – an early phase of editing and a following phase of evaluation.4 In the editing process

the agent analyses the offered prospects and simplifies them so that they can be evaluated in

the evaluation phase. The final decision is made, where the prospect of highest value is

chosen (Kahneman and Tversky, 1979).

1. Editing process – three heuristics

Representativeness

Availability

Adjustment and Anchoring

2. Evaluating phase

Value function

Probability weighting and risk attitude assessment

4 This has been proved in various occasions (e.g. Elliot and Archibald, 1989).

20

2.1.1 The Editing process

The editing phase brings some simplification to decision making. Decision maker’s cognitive

processes often involve shortcuts, so called heuristics. The complexity of assessing

probabilities of events is reduced to simpler judgmental operations by application of several

heuristic principles. They are considered to be “quite useful, but sometimes they lead to

severe and systematic errors” (Kahneman, Tversky and Slovic, 1982; p. 3).

There are three heuristics described in the PT that lead to biases in the intuitive judgment of

probability: representativeness, availability, and adjustment and anchoring.

2.1.1.1 Representativeness

When asking about the probability that A belong to B, people often rely on the degree to

which A is representative of B and are influenced by stereotypes. When applying the

representative heuristic, people often forget about several factors, e.g.:

the prior probability of outcomes

It has been shown, that when no evidence is given, prior probabilities are utilized and when

worthless evidence is given, prior probabilities are ignored.

Experiment 1(Kahneman, Tversky and Slovic, 1982):

Respondents obtained names that were reported to have been drawn from a group of 70

lawyers and 30 engineers. The respondents were asked to state the probability that this

person belongs to one of the 70 lawyers in the sample of 100 people.

- when no other information was given, the probability of a person being a lawyer

stated by respondents was 0.7

- When uninformative brief personality description about the person was given, the

probability stated was 0.5

sample size

The size of the sample plays a crucial role in the determination of the actual posterior

odds. However, people tend to ignore the sample size when judging by representativeness.

conception of chance

People wrongly expect the chance to be “fair” and “random” not only globally, but also in

every sequence generated by a random process, regardless of how short. Chance is viewed

as a self-correcting process. This approach was labelled ‘gambler’s fallacy’ (after many

blacks, red is due). The deviations are actually not corrected per se, but rather diluted.

Therefore the law of big numbers cannot be used for a sample of any size (Kahneman,

Tversky and Slovic, 1982).

21

Experiment 2 (Kahneman, Tversky and Slovic, 1982):

People in the experiment judged H-T-H-T-T-H to be more likely than H-H-H-T-T-T (which

does not appear random) and also more likely than H-H-H-H-H-H (which does not represent

the fairness of a coin)

A new term was established when examining people’s behaviour – ‘law of small numbers’. It

describes one’s tendency to assume even small samples to be highly representative of the

group they are randomly drawn from.

2.1.1.2 Availability

When using the availability heuristic, one estimates the probability of a certain event by how

easy and quickly it comes to mind.

This heuristic can lead to several biases, due to:

Retrievability of instances

The number of instances in a class will be judged by the ease with which they are retrieved or

how much they are familiar to the subject.

Effectiveness of a search set

The group which includes examples that are easier to search for will be judged to be bigger

than some others.

Imaginability

Instances are not stored in memory, but can be generated in mind using some given rule.

According to the ease with which they can be constructed, the probabilities are evaluated

(Kahneman, Tversky and Slovic, 1982).

Experiment 3 (Kahneman, Tversky and Slovic, 1982):

A group of 10 people that construct k-member groups is given.

People were instructed to mentally construct committees of k members and then evaluate their

number by the ease with which they come to mind – committees of few members (2) are more

available than of many (8). Nevertheless, the number of groups of k members equals the

number of committees of (10-k) members.

Illusory correlation (overestimating of the frequency with which two events co-occur;

could be based on the strength of the associative bond between them)

22

2.1.1.3 Adjustment and Anchoring

People can be influenced by quite a random number in their estimates. Once this initial pass at

a problem is made, one’s initial judgment may prove to be remarkably resistant to revision

(Nisbett and Ross). Adjustments are typically insufficient and underestimated.

insufficient adjustment

Experiment 4 (Kahneman, Tversky and Slovic, 1982):

Calculate the following in 5 seconds:

a)

b)

Since 5 seconds is not enough time, people had to estimate the result after a few steps of

calculation. The median for a) was 2250, for b) 512. The correct answer for both is 40 320.

This clearly shows the insufficiency of adjustments as well as that the former expression is

judged larger that the latter.

biases in the evaluation of conjunctive and disjunctive events

People overestimate the probability of conjunctive events and underestimate the probability of

disjunctive events (e.g. failure of a complex system when only one thing going wrong would

cause the problem).

anchoring in the assessment of subjective probability distributions

Variance of estimated probability distributions is narrower than actual probability

distributions. This finding is common to naive as well as expert respondents.

In addition to using heuristics in the editing phase of the decision making process, people

relate the problem and the result of the probable outcomes to some form of benchmark. The

major operations of editing process are coding, combination, segregation, cancelation,

simplification and the detection of dominance.

2.1.1.4 Coding

PT suggests that people perceive outcomes not as absolute assets, but rather code them as

gains and losses, defined relative to some neutral point. We call this point the Point of

Reference. It represents the point to which the outcome of a decision can be measured.

The reference point usually corresponds with the current asset position (status quo).

Kahneman and Tversky (1979) propose that this is the most powerful reference point and that

most people have a status quo bias. However, the location of the reference point and the

consequent coding of outcomes as either gains or losses can be affected by the offered

formulation of prospects and decision maker’s expectations (Kahneman and Tversky, 1979).

23

The following problem proposed by Kahneman and Tversky (2000) illustrates how the

framing of outcomes works, violating the requirements of invariance.

Experiment 5(Kahneman, Tversky and Slovic, 1982):

(The number of respondents was 152) Instructions: Imagine your country is preparing for the

outbreak of an unusual Asian disease, which is expected to kill 600 people. Two alternatives

to combat the disease have been proposed. Assume that the exact scientific estimates of the

consequences of the programs are as follows:

- If program A is adopted, 200 people will be saved. (72% chose this option)

- If program B is adopted, there is a one-third probability that 600 people will be saved

and a two-thirds probability that no people will be saved. (28% chose this option)

Here, the outcomes are coded as gains, measured by the number of lives saved. Respondents

are mainly risk-averse, preferring saving 200 lives for sure than risking in a gamble that offers

a one-third chance of saving 600 lives.

The same cover story was presented to another group (number of respondents 155), with

different description of alternatives:

- If program C is adopted, 400 people will die. (22% chose this option)

- If program D is adopter, there is one-third probability that nobody will die and a two-

thirds probability that 600 people will die. (78% chose this option)

The options C and D are the same in real terms as the options A and B, respectively. In the

second version, however, the outcomes are coded as losses, measured by the number of

people that will die. When evaluating options in these terms, the respondents tend to be risk-

seeking (they prefer the gamble in option D over the sure loss of 400 lives, which in terms of

gain is exactly 200 lives saved).

2.1.1.5 Combination

Combination means that prospects with identical outcomes are integrated and transformed to

a new outcome. For example, the prospect (200, 0.25; 200, 0.25) will be reduced to (200,

0.50) and evaluated in this form (Kahneman and Tverky, 1979).

2.1.1.6 Segregation

Using this operation, the riskless component of a prospect is segregated from the risky one.

Kahneman and Tversky (1979) mention this example: the prospect (300, 0.80; 200, 0.20) is

decomposed into a sure gain of 200 and the risky prospect (100, 0.80). Similarly, the prospect

(-400, 0.40; -100, 0.60) is seen as a sure loss of 100 and the prospect (-300, .40). The riskless

component is stripped away and the attention is paid to the risky aspect of the decision only.

24

2.1.1.7 Cancellation

In this stage of the editing phase, prospects that yield a common outcome are cancelled out

and do not enter the evaluation phase. According to studies, people often discard components

that are shared by the alternatives and focus on the components that distinguish them

(Kahneman and Tversky, 1979). This phenomenon is regarded to as the isolation effect.

Kahneman and Tversky (1979) offer two examples. It a two-stage sequential game, where the

first stage was common to both options, respondents evaluated the prospects based on the

results of the second stage only, the first stage was ignored.

Another example is the choice between (200, 0.20; 100, 0.50; -50, 0.30) and (200, 0.20; 150,

0.50; -100, 0.30). It can be reduced by cancellation to a choice between (100, 0.50; -50, 0.30)

and (150, 0.50; -100, 0.30).

Editing consists of the application of several operations that transform the outcomes and

probabilities associated with the offered prospects. This process can result in inconsistencies

and anomalies of preference (Kahneman and Tversky, 1979).

2.1.2 The evaluation process

Following the editing phase the decision maker evaluates each of the edited prospects. They

are then assigned a value, denoted by V. The value of an edited prospect is expressed in terms

of two scales, (or in the 1979 notation) and both defined on outcomes. assigns to

each probability of an outcome, p, a decision weight which reflects the impact of p on

the over-all value of the prospect. associates with each outcome x a subjective value of that

outcome, number . This subjective value depends on whether the individual sees the

outcome as a gain or a loss, i.e. on the reference point. Hence, the reference point serves as

the zero point of the value scale and measures the value of deviations from it (Kahneman

and Tversky, 1979).

The V is obtained by the equation:

being the outcomes

are the probabilities of outcomes;

is the value function for gains; is the value function for losses

is the probability weighting function

25

2.1.2.1 The value function

The value function represents the subjective value one assigns to outcomes. Kahneman and

Tversky (2000) propose that the utility function should be replaced with a value function

which:

a) is defined over gains and losses relative to some neutral reference point

b) is concave in the domain of gains and convex in the domain of losses

c) is steeper for losses than for gains – we label this as loss aversion

Loss aversion expresses that the response to losses is greater than the response to gains

(Kahneman and Tversky, 1986). The authors propose a rough estimate of a loss aversion

coefficient. The displeasure associated with a loss of X can be counterbalanced with a gain of

approximately 2,2X.

Outcomes are valued from a subjective reference point and framed as gains and losses. The

value function is considered to equal 0 in the reference point (see figure 4) and to have

different characteristics when in the gain domain and when in the loss domain. It is concave

for gains, while convex for losses, indicating people are risk-averse to gains and risk-seeking

when it comes to losses. In other words, people are less willing to gamble with profits than

with losses (Ghiglino and Tvede, 2000). Furthermore, the loss aversion implicates that people

are more sensitive to losses than to gains, resulting in the value function to be steeper for

losses. When these two value functions are pieced together, we obtain an S-shaped function as

in Figure 4.

Figure 4: Value function

Source: Author after Taran and Betts, 2007

26

2.1.2.2 The weighting function

According to PT, the factor incorporated with value is a psychological ‘decision weight’

rather than the mathematical probability used in EUT. The probability weighting function

transforms outcome probabilities into decision weights that may differ from actual

probabilities of outcomes (Polkovnichenko and Zhao, 2010). Its form suggested in the

original paper by Kahneman and Tversky in 1979 was modified (1992) to the form seen in

figure 5.

The individual overweighs the changes of probabilities in the left and right tails of the

outcomes distribution (the impossibility and the certainty). The difference between

impossibility and very low probability is perceived to be much bigger than the same

difference in a middle zone and has higher influence on the subjective decision weights

(analogously for the difference between very high probability and certainty). The S-shaped

form shows the tendency for people to have a systematic bias towards overweighting very low

probability events and underweighting very high probability events. The empirical support for

this shape is based on numerous experimental studies in economics and psychology (for

example, Camerer and Ho, 1994; Wu and Gonzales, 1996; Quiggin, 1987; Lopes, 1987;

Kahneman and Tversky, 1992; Prelec, 1995; Berns et al., 2007; Shoemaker, 1982; Camerer,

1995; Starmer, 2000).

The characteristics of the weighting function are consistent with examples of the EUT

violation, such as Allais effect, the common consequence effect, and the common ratio effect

(Skořepa, 2004).

Source: Author after Polkovnichenko and Zhao, 2010

Figure 5: Probability weighting function

27

2.2 Cumulative prospect theory

Cumulative prospect theory (further in the text referred to as CPT) is a new version of PT

developed by its authors Kahneman and Tversky (1992). It extends the PT in several aspects:

it is mathematically more formal, allows different weighting functions for gains and for

losses, as well as can be applied to uncertain as well as to risky prospects with any number of

outcomes, including continuous distributions (Kahneman and Tversky, 1979; Kahneman and

Tversky, 1992; Skořepa, 2004).

Probability weighting functions

Let p be a vector of probabilities of prospect A,

. These probabilities are transformed by

probability weighting functions before considered in the decision making process. Unlike the

PT, CPT operates with two different weighting functions: for the probabilities of losses

, and for the probabilities of gains (

(adapted from Skořepa, 2006b). However, Tversky and Kahneman’s (1992) study shows that

the weighting functions are actually very similar.

The theory predicts a distinctive fourfold pattern of risk attitudes: risk aversion for gains and

risk seeking for losses of high probability; risk seeking for gains and risk aversion for losses

of low probability.

Uncertain events

CPT allows to accommodate uncertainty (when probabilities are unknown) in addition to risk

(when probabilities are known). This development helps to apply the theory to a greater

variety of domains, including taxpayer decisions (Anderson, 1997), lotteries (Donkers,

Melenberg and Van Soest, 2001), racetrack betting (Jullien and Salanie, 2000), and consumer

choices among many products and features. It also leads to increased appropriateness of

utilizing methods.

Number of outcomes

CPT is able to deal with prospects with more than two outcomes. However, for prospects

containing only two outcomes, PT and CPT will give the same results. This is due to the fact

that no revision of the weighting scheme will enter into the evaluation process (Liu, 1998).

In general yield the two versions of prospect theory similar predictions, they coincide for all

two-outcome prospects. However, there are some striking dissimilarities. The cumulative

version, unlike the original one, meets the assumption of stochastic dominance. To overcome

this problem in PT, we have to assume that stochastically dominated prospects are ruled out in

the editing phase (Liu, 1998). This is no longer needed in the CPT. From another

standpoint CPT is no longer able to explain violations of stochastic dominance in

nontransparent context (Kahneman and Tversky, 1986, 2000).

28

2.3 Limitations of prospect theory

There are more models trying to explain the empirical impeachment of EUT. Among others it

is the Regret theory (Loomes and Sugden, 1982), Generalised EUT (Machina, 1982),

Disappointment theory (Gul, 1991), models RAM and TAX (Birnbaum and Chavez, 1997).

More detailed overview is offered by Camerer (1995), Starmer (2000) and Wu, Zhang and

Gonzales (2005). The prospect theory (and its cumulative version) seems to be the most

promising one. According to Skořepa (2006b) it is rich enough to explain most of the

observations regarding the decision making under risk, and at the same time not complicated

that much it would not be able to serve as the foundation stone for economic models.

Many of the results of Kahneman and Tversky’s work belong to the most mentioned and

discussed ones in the decision science (Skořepa, 2006a). PT has been applied in several areas

and has been supported by designed laboratory experiments (Chang, Nichols and Schultz,

1987; Elliott and Archibald, 1989; Fiegenbaum and Thomas, 1988; Gooding, Goel and

Wiseman, 1996; Salminen and Wallenius, 1993; Sebora and Cornwall, 1995; van Schie and

van der Pligt 1995), field experiments (e.g. List, 2004; Bolton and Lemon, 1999), surveys

(e.g. Donkers, Melenberg and Van Soest, 2001), and panel data (e.g. Mayhew and Winer,

1992).

However, it is rarely empirically tested in non-experimental situations involving real market

data. Taran and Betts (2007) point out that such reliance on experimental/survey generated

data raises concerns related to external validity of the findings, as the theory does not have

strong evidentiary support in actual practice. Suspicion in this matter raise Holt and Laury

(2002), who proved that hypothetical gains have, at least in some types of decision problems,

different impact than real gains of the same amount. Moreover, some economists believe that

refuted predictions of neoclassical model labelled as anomalies are merely the result of

mistakes made by inexperienced consumers. They suggest that these anomalies are attenuated

through time when agents obtain significant market experience (e.g. Knez et al., 1985;

Coursey et al., 1987; Brookshire and Coursey, 1987; List, 2004). Yet, this evidence also has

its critics (e.g. Knetsch and Sinden, 1987) who argue that overall the data do not conclusively

support the learning premise.

29

3 DECISION MAKING UNDER CERTAINTY

In this chapter the analysis of decision making presented in the first part of this work is

extended to riskless conditions. In a situation involving certainty, complete and accurate

information about each alternative is available and the cause and effect relationships are

known. There is only one outcome for each alternative, the same result will always occur for a

choice of strategy (The Association of Business Executives and RRC Business Training,

2008).

3.1 Microeconomic foundations of consumer behaviour

3.1.1 Basic definitions

Let be a choice set. Each option is interpreted as

a consumption bundle that offers x1 units of good A and x2 units of good B. When referred to

services, represents a service that offers x1 value level of quality

A and x2 value level of quality B. The extension to more than two dimensions is

straightforward.

3.1.2 Utility

Utility is interchangeable with happiness. It arises from the purchase of goods and services

and indicates the level of satisfaction they provide.5 The utility can be measured in terms of

‘utils’. The individual assigns a concrete level of utils to a particular good, based on the

subjective feelings. The higher the evaluation, the higher the level of utils assigned (Dowling

and Yap, 2007). Consumer’s choice arises due to the fact that his wants are unlimited, but

the sources are limited.

3.1.2.1 Total and marginal utility

The more goods and services one consumes, the greater his level of total utility (TU).

However, the increase in the utility caused by an extra unit of the same good will eventually

be decreasing. We call this the law of diminishing marginal utility (MU). The law indicates

that consumers derive less satisfaction from additional consumption (Dowling and Yap,

2007).

5 We concentrate on consumption goods and ignore investment goods – when current consumption is foregone in

favor of future consumption.

30

3.1.2.2 Utility maximization

According to microeconomics, a rational consumer tries to obtain the highest possible utility

of consumption with the least possible costs. He will always choose the consumption bundle

that maximizes his utility, given his limited income (Dowling and Yap, 2007):

,

is marginal utility of the last unit (n) of consumed good A; is the cost of A.

3.1.3 The indifference curves

A decision maker rarely evaluates things in absolute terms. He rather focuses on the relative

advantage of one good or service over another, and estimates value accordingly (Ariely,

2008).

Indifference curve (IC) represents the choice of consumption bundle for a certain level of

utility. Graphically, it can be illustrated as a curve linking all the combinations of two goods

(consumption bundles) which provide the same level of utility for a consumer. Since the level

of utility for all combinations on the indifference curve is the same, people are indifferent to

which combination they choose. The higher the indifference curve the greater the level of

utility, see figure 6. Point R provides higher utility than L and S, K provides the same utility

as L.

Source: Fuchs, 2005

Figure 6: Indifference curves

31

Indifference curve exhibits certain properties:

IC slope downwards from the left to the right; if consumer gives up some quantity of

good B, he will demand more of good A in order to keep utility unchanged – this

implies negative slopes

IC is convex and bend inwards towards the origin

ICs cannot intersect; if they did, it would violate the principle of transitivity

IC only indicates the relative preferences between different goods

The rate at which an individual is willing to exchange one unit of a good A for units of good

B without changing the IC (keeping the total utility) is known as the marginal rate of

substitution (MRS). MRS is measured by the slope of the IC: . We apply

the law of diminishing marginal rate of substitution, which is consistent with the law of

diminishing marginal utility and implies that additional consumption offers less satisfaction to

the consumer (Dowling and Yap, 2007).

3.2 Prospect theory in riskless choice

As extension of choice under conditions of risk, Tversky and Kahneman (1991, 2000)

proposed the application of prospect theory in decision under certainty. Similarly to risky

situations, PT in riskless choice operates with a value function that is S-shaped and

asymmetric (concave above the reference point and convex below it) and has three major

properties:

Reference dependence. Consumption bundles are viewed as gains and losses relative

to a reference point.

Loss aversion. Losses loom larger than corresponding gains. This results in a larger

slope of value function for gains than that for losses.

Diminishing sensitivity. The marginal value of losses and gains decreases with their

size.

3.2.1 Basic definitions

Let’s establish the reference structure that will be used in the following text. We interpret

r as ‘x is weakly preferred to y from reference state r’. The relation >r corresponds to

strict preference and =r to indifference. Every r, , is represented by a strictly increasing

continuous utility function Ur (Varian, 1984). Kahneman and Tversky (2000) describe

individual choice not by a single reference order, but by a book of indexed preference orders

{ r : }.

32

A two-dimensional graph that measures two qualities of a good or service relative to a

reference point r is used. Under these circumstances, it is more suitable to use the terms

advantage and disadvantage instead of gain and loss. We call an ordered pair

6 an advantage if and a disadvantage if .

3.2.2 Reference dependence

Determination of preferences is influenced by the reference point and its position. A shift of

reference can turn losses to gains and vice versa. In figure 7 we see two options, x and y, that

differ on two-valued dimensions. The choice between them is affected by the reference point

they are evaluated from.

Source: Author after Kahneman and Tversky, 1991

Although the reference state usually corresponds to the decision maker’s current position, it

can be influenced by expectations, aspirations, norms, and social comparisons (Kahneman

and Tversky, 2000).

3.2.3 Loss aversion

“Loss aversion implies that the impact of a difference on a dimension is generally greater

when that difference is evaluated as a loss than when the same difference is evaluated as a

gain” (Kahneman and Tversky, 2000; p.145). For better understanding, see the graphic

illustration in figure 8.

6 [xi, ri] indicates a pair, whereas (x1,x2) represents a two-dimensional option.

Figure 7: Multiple reference points for the choice between x and y

33

We operate with four points: s, r being reference states and x, y denoting options that differ on

two-valued dimensions. Suppose that and ; and ; and

. Then the following holds:

s implies that, relative to the reference state s, the combination of the advantage

and the advantage has the same impact as the combination of the

advantage and the null interval .7

r implies that, relative to the reference state r, the combination of the advantage

and the null interval has greater impact than the combination of the

advantage and the disadvantage .

Moving from s to r, the reference state and also the preferences change. The disadvantage

enters into the evaluation of y and the advantage

disappears from the evaluation of x. The change in both evaluations has the same size of

, it differs by sign only. Hence, the individual should stay indifferent. The fact that

the introduction of a disadvantage has greater impact than the deletion of advantage of

the same size signifies the loss aversion.

Loss aversion implies that for all x, y, r, s, in X holds: suppose that

as shown in figure 8. Then s implies that r . This means that the

slope of the IC through y is steeper when evaluating y from r than from s. To put it in terms of

MRS, , where is the marginal rate of substitution of Ur at y

(Kahneman and Tversky, 2000).

7 Since y1=s1, we can replace the interval [y1, s1] with [y1, y1] to emphasize the null effect.

Source: Author after Kahneman and Tversky, 1991

Figure 8: A graphic illustration of loss aversion

34

3.2.3.1 The effect of different reference points on a preference

The choice between two options, x and y, is affected by the position of reference point they

are evaluated from. The relative weight of differences between x and y on two attributes

changes with the location of the value of reference point on these dimensions and this causes

the reversal of preference (Kahneman and Tversky, 2000).

The evaluation of the options x and y in figure 7 from reference points r, r' is done as follows:

When evaluated from r, option x represents solely an improvement on dimension 1,

i.e. an advantage , whereas y combines an advantage in dimension 2

with a disadvantage in dimension 1 .

When evaluated from r', the relations are reversed: option y is simply an advantage on

dimension 2 , x is a combination of an advantage in dimension 1

and a

disadvantage in dimension 2 .

Assuming the loss aversion, we are able to come to these conclusions:

x is more likely to be preferred from r than from r'

y is more likely to be preferred from r' than from r

When evaluated from r, x is more likely to be preferred over y

When evaluated from r', y is more likely to be preferred over x

Experiment 6 (Kahneman, Tversky and Slovic, 1982):

106 participants were presented a situation where they had to imagine they were assigned to

a part-time job that was ending. Two possibilities for a new employment were considered, job

x and job y. The three jobs with their differences are described in the following table:

Social contact Daily travel time

Present job isolated for long stretches 10 minutes

Job x limited contact with others 20 minutes (chosen by 70%)

Job y moderately sociable 60 minutes (chosen by 30%)

Both options are superior to the current job in social contact (which is evaluated as an

advantage) and both are inferior in commuting time (evaluated as a disadvantage).

Loss aversion signifies that a difference between two options will be given greater weight

when it is evaluated as a difference between two disadvantages (relative to a reference state)

than if it is seen as a difference between two advantages. Respondents preferred option x with

smaller gain than y in one dimension, but at the same time with smaller loss in the second one

(relative to the present job) (Kahneman and Tversky, 2000).

35

3.2.3.2 Status quo bias

The status quo (SQ) bias, introduced by Samuelson and Zeckhauser (1988), relates to the loss

aversion. It induces that an individual favours the retention of his status quo over other

options. The SQ bias is a consequence of the asymmetry showed in experiment with jobs: the

disadvantages of a change seem larger than its advantages. As shown in figure 7, due to the

status quo bias, a decision maker indifferent between x and y from reference state t will prefer

x over y from x and y over x from y (Kahneman and Tversky, 2000).

Samuelson and Zeckhauser (1988) documented this bias in a series of studies and

experiments. They observed that small changes of status quo were favoured over larger

changes. They see the SQ bias as explanation of a brand loyalty and pioneer firm advantage.

They mention several factors that can lead to status quo bias even in the absence of loss

aversion, e.g. costs of thinking, transaction costs, or psychological commitment to prior

choices.

3.2.3.3 Endowment effect

Endowment effect shows that the loss of utility associated with giving up a valued good that

is already in one’s endowment is greater than the utility gained by receiving it (Thaler, 1980).

Kahneman, Knetsch and Thaler (1990) proved this in a several experiments. It refers to

people's unwillingness to give up property they already own. Kahneman and Tversky (1991)

see this as the reason for a gap between buyer price and seller price. When giving something

up (e.g. selling it), people may see this as a disturbance and ask for compensation, therefore

demanding a higher price than they would have if they were to buy the product.

The reluctance to buy is not as big as the reluctance to sell. This is because people don’t treat

money as a good worth keeping but rather as a means for purchasing goods. Deciding whether

or not to buy a good does not mean deciding between buying the product and keeping money,

it is actually a choice between spending the money on this good and spending it on other

goods that could be purchased instead (Kahneman and Tversky, 2000).

3.2.4 Diminishing sensitivity

The diminishing sensitivity can be interpreted as: the more the options are remote from

a reference point, the lower the impact of the change for the relevant dimension. People

perceive the difference between a €10 and a €5 discount with a larger impact than the

difference between a discount of €105 and a €100. This directly leads to a concave value

function in the gain domain and convex in the loss domain (Liu, 1998).

36

4 PROSPECT THEORY IN MARKETING

Prospect theory has become one of the most widely cited theories and has been applied in a

variety of areas including economics, finance, decision sciences, political science,

management etc. It has also been applied to marketing, although such studies are relatively

few compared to other application areas (Liu, 1998).

The task of marketers is to understand how and why people’s behaviour deviates from

rational decision models (Bernstein, 1997). Very frequent applications of the PT in marketing

have been decisions involving money, such as prices, discounts, coupon promotions,

advertising, monetary incentives including sales force compensation and product bundling

(Jagpal, 1999; Stremersch and Tellis, 2002; Johnson, Herrmann and Bauer, 1999). Most

widely used is the PT in pricing with the use of reference point (Erdem, Mayhew and Sun,

2001; Niedrich, Sharma and Wedell, 2001).

According to Prospect Theory, people will edit an option before evaluating it (Kahneman and

Tversky, 1979). This has been proved in various occasions (e.g. Elliot and Archibald, 1989).

In the editing phase, people code the alternatives into gains or losses according to some

reference point. When then faced with a purchase decision, there is evidence that losses have

greater impact on choice than gains (e.g. Novemsky and Kahneman 2005a; Novemsky and

Kahneman 2005b; Thaler et al., 1997; Kahneman and Tversky, 1991). In order to predict

people's choices, the position of the reference point needs to be known. The issue of the

location of the reference point was first addressed by the research on reference price (Liu,

1998).

The reference price concept suggests a reference price as a standard to which a purchase

price of a product is compared (Monroe, 1979). People can only hardly evaluate how much

things are worth in absolute terms. They do not judge prices in isolation but rather by

comparing them to their internal reference point.

Adaptation-Level Theory (Helson, 1964) provided the original theoretical basis of the

reference price concept. It postulates that people have an adaptation level (reference point)

based on their past experiences (e.g., price of the last purchase) and environmental factors

(e.g., price seen in advertisements).

The theory also addresses the choice of reference proposing that consumers can shift their

reference point if adequately compelled to do so. This indicates that there may be multiple

reference points. For example, in establishing the reference point for the quality of a product,

one might look at all the products, a class of products, ‘price-quality tiers’ (Lemon and

Nowlis, 2002), or the brand (following the well researched brand effects (e.g. Betts and

Taran, 2004)).

37

As pointed out above, heterogeneity of consumer segments might lead to several reference

points upon aggregation. Taran and Betts (2007) show that the information providers as well

as the stores/brand owners can influence the formation of people’s reference points by

external categorization schemes (such as, Consumer Reports’ classes).

The main idea of reference point is that the way in which people value things depends on

what they compare them to. Moreover, according to Ariely (2008), people tend to focus on

comparing things that are easily comparable – and avoid comparing things that cannot be

compared easily. This finding could be used in marketing when the position of reference state

is tried to be influenced.

Although called a "point", it has been found that reference point is actually an area of

acceptance. This area is insensitive – consumer will not react to any changes within it. Only

moving outside the area will result in a different outcome. When the loss aversion principles

are applied, the area tends to be asymmetric around the traditionally defined reference point,

smaller in loss domain and larger in gain domain (Liu, 1998).

People code outcomes as gains and losses. However, the message framing may not be

identical in all circumstances and choices may be influenced by other factors. Schoemaker

(1982) and Woodside and Singer (1994) found that the decision outcome could be influenced

by verbal labels, modes of information presentation, social dimensions, and response modes.

Source: Author after Liu, 1998

Figure 9: Area of acceptance

38

SUMMARY OF THE THEORETICAL PART

The neoclassical model of expected utility theory has been proven to be insufficient in

explaining all the aspects of individual’s decision making process. Its basic assumptions are

consistently violated and its concept of a rational agent has been proved by several studies to

be inadequate.

An alternative theory that could explain anomalies in one’s decision behaviour is Prospect

theory, introduced by Kahneman and Tversky (1979). Kahneman and Tversky included

psychological effects into their model and found out that the irrationality in agent’s decisions

has some consistency and follows certain rules. According to the prospect theory, decision

makers do not calculate with the absolute value of outcomes but rather compare them against

a reference point. Relative to this reference point, the alternatives are then coded as gains

(above the reference point) or losses (below the reference point). Gains and losses are

weighted by their perceived probabilities, forming a non-linear value function. People

approach gains and losses differently, generally being risk-averse for gains and risk-seeking

for losses. This results in the ascertained shape of the value function to be concave over gains

and convex over losses. PT further posits that the degree of risk aversion above the reference

point is greater than the risk seeking below it.

Prospect theory has helped to explain many of the behaviour patterns that could not be

adequately explained by expected utility theory. The prospect theory has received widespread

acceptance due to its intuitive appeal and theoretical as well as empirical support. It has been

theoretically developed into Cumulative Prospect Theory (Kahneman and Tversky, 1992) and

Prospect Theory under Certainty (Kahneman and Tversky, 1991). Thaler (1985) has extended

Prospect Theory to another widely used theory – Transaction Utility Theory.

Even though the theory seems promising, its potential is still not revealed. There are many

laboratory experiments testing and supporting its validity. Nevertheless, the use of the

theoretical principles in praxis is limited. There is lack of research done on application of the

theory in market field. The decision maker’s behaviour can be explained ex-post with the help

of PT, but not yet predicted.

39

II Practical part

As discussed in Chapters three and four, there is a lack of studies that focus specifically on

using the prospect theory in marketing and promoting. Therefore, this thesis was designed to

descriptively survey the behaviour of consumer’s when faced with an offer constructed on the

prospect theory principles. In the practical part of this paper, the author introduces the

research question and hypotheses. To test the hypotheses, the thesis is structured to fulfill two

objectives using appropriate research methodology. The empirical study is conducted for and

applied to a concrete company, a travel agency, which is introduced in the second chapter of

this part. The author creates two questionnaires, both containing destinations from the travel

agency’s offer. The options for each question are chosen to reflect the prospect theory

principles. The conducted survey tests whether affective responses to hypothetical destination

offers would be consistent with the prospect theory’s loss aversion principle. The data are

compared and analyzed and consequently the results of the research are reached. A suggestion

for the company is formulized, how the prospect theory could be applied in its marketing.

5 PROJECT GOALS & OBJECTIVES

5.1 Research question

The purpose of the research presented in this thesis is to answer the following research

question:

Will the use of prospect theory in an offer affect customer’s choice?

The benefit of answering the research question is significant for marketers. In order to be able

to advertise a product or a service, a marketer has to understand the customer’s behaviour.

This research might have impact on perceiving the cues consumers use to infer which

products or services are superior to others. Hence, the formation and changing of consumer

attitudes toward products or services could be predicted. This research will help in the

development of marketing and promotional tools. It could lead to a broader application of

prospect theory in marketing strategies of product sellers and service providers.

5.2 Objectives

The objectives of this thesis are to:

1) Analyze service merchantability in a concrete company and to identify the possibilities of

improvement

2) Propose an application of prospect theory in marketing of the chosen company that will

lead to the desired improvement

40

5.3 Hypotheses

Based on the research question, following hypotheses are set up:

H1: The shift of reference point will cause a change of preference.

H2: Customers with strict preference do not act as loss averse. The loss aversion principle

has greater impact on indifferent subjects.

H3: The application of prospect theory principles in the company’s marketing will lead to the

desired improvement.

The acceptance or rejection of the hypotheses is allowed by analyzing of collected data. In

order to collect and analyse the data needed, several research methods are used.

5.4 Research methodology

To achieve the first objective, a travel agency is chosen as the subject for empirical study.

Research methods used here are observation, description, studying internal company

information sources and personal in-depth interview with manager responsible for marketing

of the company.

The second objective of the thesis is met through an empirical survey, using two

questionnaires with a multiple choice questions format. The methods used are personal

interview with the company manager in order to find out the needs of the company,

conduction of an empirical survey, data collection, objective measurements, statistical

analysis in a statistical software STATISTICA 10, data and results evaluation, analyses of

merchantability of services and their changes by using appropriate instruments: assimilation

of internal data from previous economic period and the answers from empirical survey, and

synthesis.

41

6 INTRODUCTION OF PUXTRAVEL

6.1 History of the company

PUXtravel is an internet travel agency founded in 2003 in Brno, Czech Republic, under the

name pux, s. r. o. (limited company).8 To the Register of Companies was the agency

registered in January, 2004. The founders of the company were MUDr. Ing. Mgr. Karel

Kameník, the executive head, Ing. Mgr. Tomáš Hložánek, the executive head and Petr

Kameník, the web- and graphic designer. Besides the travel agency PUXtavel

(http://www.puxtravel.cz/), the pux family includes also PUXpub (http://www.puxpub.cz/), a

restaurant in Brno, graphic studio PUXdesign (http://www.puxdesign.cz/) and virtualPUX

(http://www.virtualpux.com/), which specializes in visualisation of commercial

accommodation and offers creation of virtual interior tours. As of December 31, 2011,

PUXtravel employs 7 employees in Czech Republic.

6.2 Vision, mission and principles of PUXtravel

The PUXtravel’s mascot is a gorilla with a slogan: “because it does not matter who you are ...

all that counts is that you love snow and mountains!”9 The long term objective is to be one of

the cheapest travel agencies on the Czech market. The philosophy of the company can be

captured in eight points:

Low price

Open approach towards the clients

Honest and fair dealing with clients

Professional and good-quality service

Continuous progress

Colourful tours full of energy

High intellectual level of employees

Company’s pride

8 Jaselská 11, 602 00 Brno, Czech Republic. IČ: 26915545, DIČ: CZ 26915545.

9 For a commercial spot, see http://www.youtube.com/watch?v=I0pyhfOWE4o&feature=relmfu.

42

6.3 Services

PUXtravel offers services of winter and summer trips as well as additional actions off the

main season. The main focus of the company lies on the winter season, the offers being skiing

and snowboarding tours for individuals, organized collective tours for companies and schools

and winter schools of skiing and snowboarding taught by certified instructors of PUXtravel.

The skiing destinations in the offer are Alps (France, Italy, Austria, and Switzerland) and

Carpathians (Slovakia and Rumania). PUXtravel is an internet company; all the tours can be

found and ordered online. The entire offer with pricelist and the relevant information about

the tours is listed on the homepage http://www.puxtravel.cz/. For its tours, the travel agency

supplies following services:

Transportation to the destination. There is an option of a bus service from Czech cities

– Prag, Brno, and Plzeň.

A Delegate

Arranging of travel insurance

Accommodation (hotels, apartments, pensions) with or without board

Ski pass

Ski instructor (if required)

A possibility to view some of the apartments online via virtual 3D tour

6.4 Features and trends

When choosing a winter skiing tour, the customers take several factors under consideration:

1. PRICE of the accommodation, ski pass, transportation, boarding

2. SKI SLOPE KILOMETRES

3. SKI SLOPE PARAMETRES and PROPORTIONS of blue, black, red and green

slopes

4. TYPE AND NUMBER of cabins, chairlifts and ski tows

5. THE DISTANCE FROM ACCOMODATION TO SKI SLOPE

6. THE DISTANCE FROM CZECH REPUBLIC TO FINAL DESTINATION

7. WEATHER CONDITIONS

8. ACCOMMODATION (hotel, apartment, half-board or all inclusive, additional

service: wellness, sauna, swimming pool, fitness)

9. AVAILABILITY in different terms etc.

43

Customers evaluate each resort according to its qualities in these factors and then make a

decision reflecting their individual preferences. Based on the agency’s experience, the two

most visited resorts are in France and Austria. Each country offers different attributes to the

skiers.

The French resorts are generally considered to be of a good quality, with one negative side for

Czech and Slovak skiers being the long travel distance. Compared to Austria, the

accommodation is not as spacious, but the prices are lower. The hotels are built in the walking

distance from ski slopes, usually within 500 metres. The weather conditions promise reliable

sunny weather most of the time. Most French Alps resorts offer more than 100 kilometres of

wide ski slopes, resorts with less than 60 kilometres are only occasional. To the best and most

visited resorts in France belong Trois Vallées with 600 ski slope kilometres (Les Menuires,

Val Thorens, Meribel, La Tania and a luxury Courchevel), Portes du Soleil with 650 ski slope

kilometres, Chamomix/Mont Blanc with 420 ski slope kilometres, Alpe d’Huez with 240 ski

slope kilometres, Les Arcs with 200 ski slope kilometres and Risoul/Vars with 180 ski slope

kilometres.

Austria is a popular destination for many Czechs mainly for its accessibility from Czech

Republic. Compared to France, services offered in Austria are of a higher level and the prices

are adequate to their quality. Accommodation is of a high standard, mostly in roomy

apartments. These are located in small villages near to ski slopes, with the need to use a car or

a ski bus to reach them. Weather in Austria can vary, rainy days are often and good weather

conditions cannot be guaranteed. Austrian Alps offer 215 ski resorts, which is the most in one

country in the world. They are smaller than the French ones, with first class facilities and ski

slope surfacing and maintenance. Among the best resorts in Austria can be found Schladming,

with 167 ski slope kilometres, Zell am See, with 137 ski slope kilometres, Stubaital with 108

ski slope kilometres, St. Anton, St.Christoph and Stuben, 133 ski slope kilometres and

Zillertal with 159 ski slope kilometres.

44

6.5 Analysis of the current situation of service merchantability

The market of winter travelling in Czech Republic is lead by the biggest company Nev-Dama,

a. s. which is the price maker. Other travel agencies set their prices based on the prices of

competition. The profit margin is then defined based on the price discounts ski resorts offer to

winter tour operators and travel agencies. The profit margin of PUXtravel’s tours is

approximately 15 % for each country. The best conditions for the company are in France,

with discounts of 30-40 % from public prices. The discounts that the agency gets are reflected

in lower prices for customers rather than bigger profit for the company. In Italy or Austria

these discounts are only around 10 %. With the profit margin of 15 % this means the prices of

tours are higher than one would get as an individual. People ordering tours in Austria have

therefore tendency to use the agency’s service only once. When they realize they could

arrange it cheaper, they settle with the accommodation owner and next time travel on their

own. Numbers of customers of the last four seasons for each country are captured in table 2.

Table 2: Numbers of PUXtravel customers for each country

Year

Country

2008 2009 2010 2011

France 2344 2600 3004 2970

Austria 696 860 617 1207

Italy 870 509 498 617

Others 44 - 8 6

Overall 3954 3969 4127 4800

Source: PUXtravel internal information

The number of clients of the agency is increasing every year. In the last season (2011) the

total number of PUXtravel’s customers was 4800, 60 % of which had already used services of

the agency before and 40 % were new clients. Customers interested in the French destinations

decreased in the last season, whereas the number of visitors of Austria almost doubled, from

617 in 2010 to 1207 in 2011. In graph 1 the numbers of clients from table 2 are calculated into

quotients and the growing/falling tendency is showed. As seen in the graph, the percentage of

customers choosing French resorts has fallen from 72.8 % in 2010 to 61.9 % in 2011. This

proportion has been changed in favour of Austrian destinations, where the percentage has

increased from 15 % in 2010 to 25.1 % in 2011.

45

Graph 1: Percentages of PUXtravel customers for each country

Source: PUXtravel internal information

Table 3 captures the proportion of France to Austria clients, clients of other resorts are not

taken into account. The rate of France to Austria has fallen from 83:17 in 2010 to 71:29 in

2011.

Table 3: Proportion of clients travelling to France and Austria

2008 2009 2010 2011

France 2344 77.1 % 2600 75.1 % 3004 83.0 % 2970 71.1 %

Austria 696 22.9 % 860 24.9 % 617 17.0 % 1207 28.9 %

Overall 3040 100 % 3460 100 % 3621 100 % 4177 100 %

Source: Author based on PUXtravel internal information

According to the results of surveys made by PUXtravel among its clients10

, this tendency is

due to the long travel distance from Czech Republic to France. Even though the service in

France is cheaper in comparison to Austria, people seem to start to value the conformity of

travelling to the neighbour country more. The PUXtravel’s long-term strategy is to gain more

customers for France, where the agency is able to offer lower prices for the tours than

customers would get on their own. The required improvement the agency aims is at least the

situation as in the year 2009, i.e. the rate 75:25.

10 PUXtravel conducts questionnaires and these are handed out to the customers in buses (response rate in 2011

56,55%) and to those who travel individually the forms are sent by email (response rate approximately 5-10%).

0,0%

10,0%

20,0%

30,0%

40,0%

50,0%

60,0%

70,0%

80,0%

2008 2009 2010 2011

59,3%

65,5%

72,8%

61,9%

17,6% 21,7%

15,0%

25,1% 22,0%

12,8% 12,1% 12,9%

1,1% 0,0% 0,2% 0,1%

France

Austria

Italy

Others

46

7 EMPIRICAL SURVEY

7.1 Research approach

Based on a personal interview with Tomáš Hložánek, four factors out of those listed in section

6.4 were selected. These are considered to be the most significant for customers when

choosing a ski resort.

1. PRICE of the ski tour (including accommodation, ski pass, transportation)

2. SKI SLOPE KILOMETRES

3. THE DISTANCE FROM ACCOMODATION TO SKI SLOPE

4. THE DISTANCE FROM CZECH REPUBLIC TO FINAL DESTINATION

Out of these four characteristics of each resort, three two-dimensional graphs are constructed.

The loss aversion and reference point principles are used. Each graph contains two points

lying on the same IC – resort options Xi (Austrian resort) and Yi (French resort). Each of the

options exceeds in one attribute off the other. The following holds for the points Xi (x1, x2)

and Yi (y1, y2): . The two attributes on axis reflect the IC characteristics –

the bigger the point coordinates of an option on the axes, the better the option. Since the focus

is at the preference between French and Austrian resorts only, one dimension in all the graphs

is the distance from Czech Republic to final destination (Austria or France). The second

dimension reflects one of the three remaining resort characteristics for each graph:

1. Price – resorts X1 and Y1 are of the same ski conditions and size, the distance from

accommodation to ski slopes is the same. The choice is between a more expensive

resort in close Austria (X1) and a cheaper resort in more distant France (Y1).

Quality A being the distance from Czech Republic and quality B being the price, the

construction of the graph is as follows. As the resort X1 is closer to Czech Republic than

Y1 (i.e. X1 is better in the quality “distance” than Y1), the point X1 will have higher

coordinate in quality A than Y1. The resort Y1 is cheaper (better in the quality “price”)

than X1, i.e. will have a higher coordinate in B than X1.

2. Ski slope kilometres – the price of ski tour in resort X2 and Y2 is the same, the

distance from accommodation to ski slopes is the same. The choice is between a

smaller resort in close Austria (X2) and a bigger resort in more distant France (Y2).

3. The distance from accommodation to ski slope – the price of ski tour in resort X3

and Y3 is the same, resorts X3 and Y3 are of the same ski conditions and size. The

choice is between a resort with accommodation distant from the ski slope in close

Austria (X3) and a resort with accommodation near the ski slope in more distant

France (Y3).

47

To each of the three graphs, a reference point, Xi- or Yi

-, is added. Each type of graph has now

two versions, one with options Xi, Xi- and Yi and the second one with options Xi, Yi, Yi

-. For

adding the third resort, the loss aversion principle described in chapter 3 is applied. The point

Xi- (or Yi

-) is worse than Xi (or Yi) in one dimension and of the same level in the second one.

The predictions are that and

. The figures are illustrated below.

Figure 10: The illustration of options X1 and Y1 with the shift of reference point

Figure 11: The illustration of options X2 and Y2 with the shift of reference point

Figure 12: The illustration of options X3 and Y3 with the shift of reference point

Source: Author

48

7.2 Survey Design

Based on the two reference points in the three graphs illustrated above, two versions of

questionnaire – A and B – are constructed to be compared to each other. Both survey

questionnaires are divided into two parts: resort issues and demographics issues. Each of the

questionnaires contains three questions about preferences among destinations offered with an

additional question about the decision weight of the four factors mentioned in section 7.1, and

three questions collecting demographic information. The survey questions were developed

from the travel agency’s offer accessible online till February 13, 2012.

For each graph type, the questionnaire A includes one question, either Xi, Yi, Yi-, or Xi, Xi

-, Yi.

Questionnaire B is then designed to contain pair questions to questionnaire A, with the

reference point that was not used in the questionnaire A, either options Xi, Yi, Xi-, or Xi, Yi,

Yi-. Question 1 in both questionnaires contains options that differ by their price, question 2

includes resorts that differ by the ski slope kilometers and question 3 offers options that differ

by the distance from accommodation to the ski slope. The purpose of this design is to observe

and compare the respondents’ preferences when the options Xi, Yi are evaluated together with

the point Yi-, and when containing the option Xi

-. A copy of the surveys in Czech and English

is included in Appendix.

7.3 Data

Two audiences were surveyed to evaluate the resorts and identify destination preferences. The

audience A were internet respondents and the group B were PUXtravel’s customers. This

approach leads to more informative answers and provides a better understanding of the

preferences.

In the group A, four hundred twenty six people were contacted via email and internet site

http://www.vyplnto.cz, out of which 332 responses were collected (78 percent response rate

for the A questionnaire). The group B was selected from the PUXtravel contacts database and

was sent the link to the online survey. Out of a random sample of 1500 PUXtravel customers

surveyed, 314 participated in the survey (21 percent response rate).

49

7.4 Survey results and analysis

The subjects surveyed were asked to indicate whether they preferred their preferences among

options offered in the questions. The results are compared to the last year’s numbers, where

the French destinations were preferred to the Austrian ones in the rate of 71 to 29, see table 3.

The application of prospect theory aims improvement of this rate in favour of France. This is

tested on the questions containing options Xi, Yi, and Yi-. If people are averse to giving up the

possibility to gain an improvement, as implied by loss aversion, then the preference of Yi over

Xi should be more common among the respondents whose reference point was Yi-. The effect

of the theory is confirmed on the pair questions containing options Xi-, where the rate is

expected to be changed in favour of Austria.

7.4.1 Question 1

Table 4 and 5 show the answers to question 1 for questionnaire A and B. Both contained the

same destinations X1, Y1, that differed by price. The third option was different for each

questionnaire – questionnaire A had an Austrian resort X1-

as a reference point, whereas

questionnaire B offered a French resort Y1-. As seen in the table 4, when the reference point is

the worse Austrian resort, people incline to the better Austrian resort – Hotel Steuer. In group

A, 39.2 % of respondents chose Steuer, whereas the cheapest Foret Blanche chose 53.3 %. In

group B, the numbers changed due to the shift of reference. In comparison to the worse

French option looks Foret Blanche more interesting, 68.2 % of respondents in group B chose

this option. The attractiveness of Steuer has fallen to 19.7 %.

Table 4: Answers to question 1, group A

Option Destination Number of respondents

X1 Ski resort Dachstein West, Austria

Hotel Steuer, Price Kč 11,810 130 (39.2 %)

Y1

Ski resort Risoul/Vars, France

Hotel Foret Blanche, Price Kč 9,580 177 (53.3 %)

X1- Ski resort Dachstein West, Austria. Hotel Musik.

Price Kč 12,300 25 (7.5 %)

Source: Author based on survey results

50

Table 5: Answers to question 1, group B

Option Destination Number of respondents

X1 Ski resort Dachstein West, Austria

Hotel Steuer, Price Kč 11,810 62 (19.7 %)

Y1

Ski resort Risoul/Vars, France

Hotel Foret Blanche, Price Kč 9,580 214 (68.2 %)

Y1- Ski resort Risoul/Vars, France

Hotel Antares, Price Kč 11,080 38 (12.1 %)

Source: Author based on survey results

The comparison of the results for destinations X1 and Y1 is captured in graph 2. As seen in the

graphs, the number of subjects who chose Y1 over X1 has increased when the two options

were presented together with Y1- in questionnaire B rather than X1

- in questionnaire A. This

result is consistent with prospect theory assumptions.

Graph 2: Answers to question 1, comparison of group A and B

Source: Author based on survey results

The options in question 1 differ by price. To distinguish the effect of the lowest price from the

loss aversion effect, the data are analysed according to the decision weight of the factor price.

When the most important factor by decision making process is the price, people choose the

cheapest offer. The prospect theory is not expected to have much influence on the price

sensitive respondents as they do not need to decide. They know what they want already. In

table 6, the answers of price sensitive (those who stated that price is the most significant

decision factor for them) and price indifferent respondents (those who stated the importance

of resort’s price is on the 2nd

, 3rd

, or 4th

place) of questionnaire A are captured.

39.2 %

53.3 %

7.5 %

Steuer

Foret Blanche

Musik

19.7 %

68.2 %

12.1 %

Steuer

Foret Blanche

Antares

51

Table 6: Preferences of price sensitive vs. price indifferent respondents, group A

Option Price sensitive respondents Price indifferent

respondents

Steuer (X1) 46 (29.5 %) 84 (47.7 %)

Foret Blanche (Y1) 106 (67.9 %) 71 (40.3 %)

Musik (X1-) 4 (2.6 %) 21 (11.9 %)

Source: Author based on survey results

The cheapest option is Foret Blanche; the price sensitive respondents who are looking for the

lowest price would prefer this resort over the Austrian ones. 29.5 % of price sensitive

respondents chose the more expensive Steuer. The loss aversion effect is more significantly

evident on the price indifferent subjects. Here the preference for Steuer, which was aimed for,

is achieved. Price indifferent respondents make decision comparing the cheap, but distant

French resort with the Austrian close, but more expensive one. The loss aversion caused the

Steuer choice of 47.7 % of these respondents.

Table 7 shows the answers of respondents in group B. The percentage of price indifferent

respondents choosing Foret Blanche rises from 40.3 % in group A to 61.1 % in group B. On

the other hand, the price indifferent respondents choosing Steuer has fallen from 47.7 % in

group A to 19.4 % in group B. The shift of preference from Steuer (A) to Foret Blanche (B) is

due to the change of reference point. For the price sensitive respondents, the loss aversion

effect is supported by the fact that the aimed option is also the one with the lowest price. The

number of subjects choosing Foret Blanche is therefore higher than for price indifferent

respondents, namely 74.1 %.

Table 7: Preferences of price sensitive vs. price indifferent respondents, group B

Option Price sensitive respondents Price indifferent

respondents

Steuer (X1) 34 (20.0 %) 28 (19.4 %)

Foret Blanche (Y1) 126 (74.1 %) 88 (61.1 %)

Antares (Y1-) 10 (5.9 %) 28 (19.4 %)

Source: Author based on survey results

Table 8 shows the loss aversion effect in group B. Respondents who indicated the distance

from Czech Republic is the most important factor to them, when deciding about their ski

holidays, are less affected by the position of reference point. The Austrian destination chose

50 % of country sensitive subjects due to the fact it is close to Czech Republic. Country

indifferent respondents can be labelled as loss averse. Choice of Austrian Steuer falls to

16.3 % and 70.2 % of the subjects prefer Foret Blanche.

52

Table 8: Preferences of country sensitive vs. country indifferent respondents, group B

Option Country sensitive

respondents

Country indifferent

respondents

Steuer (X1) 16 (50.0 %) 46 (16.3 %)

Foret Blanche (Y1) 16 (50.0 %) 198 (70.2 %)

Antares (Y1-) 0 (0.0 %) 38 (13.5 %)

Source: Author based on survey results

7.4.2 Question 2

The answers to question 2 of both questionnaires are captured in tables 9 and 10. Destinations

X2 and Y2 differ by the ski slope kilometres of the ski resorts. The reference point was

different for each questionnaire – questionnaire A contained an Austrian resort X2-

and

questionnaire B offered a French resort Y2-.

Table 9: Answers to question 2, group A

Option Destination Number of respondents

X2 Ski resort Dachstein West, Austria

Hotel Promberg, 130 ski slope kilometres

112 (33.7 %)

Y2

Ski resort Les Menuires/Trois Vallées, France

Hotel Croisette, 160 ski slope kilometres

167 (50.3 %)

X2- Ski resort Pitztal, Austria

Hotel Planger, 48 ski slope kilometres

53 (16.0 %)

Source: Author based on survey results

Table 10: Answers to question 2, group B

Option Destination Number of respondents

X2 Ski resort Dachstein West, Austria

Hotel Promberg, 130 ski slope kilometres

62 (19.7 %)

Y2

Ski resort Les Menuires/Trois Vallées, France

Hotel Croisette, 160 ski slope kilometres

236 (75.2 %)

Y2- Ski resort Les Orres, France

Hotel La Combe d´Or, 88 ski slope kilometres

Price 12.300 Kč

16 (5.1 %)

Source: Author based on survey results

53

The comparison of the results of group A and group B is shown in graph 3. People tend to

change their preference with the shift of the reference point. In group B, where the reference

is Y2-, 75.2 % of the respondents chose Croisette. In group A this number falls to 50.3 %

because of the different third option, X2-. Next to X2

-, Promberg looks superior and this option

got 33.7 % of all answers in group A. When La Combe d’Or was in the offer, Promberg was

chosen by only 19.7 % of all B group respondents.

Graph 3: Answers to question 2, comparison of group A and B

Source: Author based on survey results

Croisette (Y2) offers the most ski slope kilometres of all the offers. To isolate the prospect

theory effect on the choices, the data are disposed based on the decision weight of the factor

ski slope kilometres. In table 11, the A-group respondents are divided into those who stated

the number of ski slope kilometres is the most important factor to them (number 1 was

assigned to this factor) and those to whom this factor is not that important (numbers 2, 3, or 4

were assigned).

Table 11: Preferences of ski slope sensitive vs. ski slope indifferent respondents, group A

Option Ski slope sensitive

respondents

Ski slope indifferent

respondents

Promberg (X2) 9 (26.5 %) 103 (34.6 %)

Croisette (Y2) 20 (58.8 %) 147 (49.3 %)

Planger (X2-) 5 (14.7 %) 48 (16.1 %)

Source: Author based on survey results

The ski slope sensitive respondents prefer Croisette over Promberg, the effect of loss aversion

is suppressed. Compared to these results, ski slope indifferent respondents are more affected

by the reference point. The number of people choosing Promberg rises to 34.6 %, whereas the

number for ski slope sensitive respondents is 26.5 %. French Croisette with 160 km of ski

33.7 %

50.3 %

16.0 %

Promberg

Croisette

Planger

19.7 %

75.2 %

5.1 %

Promberg

Croisette

La Combe d´Or

54

slopes prefers 49.3 % of the ski slope indifferent respondents in comparison to 58.8 % of ski

slope sensitive ones.

Table 12 shows the answers of respondents in group B. The percentage of respondents

choosing Croisette is higher than in group A, both for ski slope sensitive respondents (76.7 %

in group B compared to 58.8 % in group A) and ski slope indifferent respondents (74.6 % in

group B in comparison to 49.3 % in group A). This is caused by the shift of reference point.

Croisette is preferred by ski slope sensitive (76.7 %) as well as ski slope indifferent

respondents (74.6 %).

Table 12: Preferences of ski slope sensitive vs. ski slope indifferent respondents, group B

Option Ski slope sensitive

respondents

Ski slope indifferent

respondents

Promberg (X2) 12 (14.0 %) 50 (21.9 %)

Croisette (Y2) 66 (76.7 %) 170 (74.6 %)

La Combe d´Or (Y2-) 8 (9.3 %) 8 (3.5 %)

Source: Author based on survey results

In table 13 the respondents of group B are divided into two columns based on their attitude

towards the factor of travel distance from Czech Republic. As in question 1, the respondents

who stated the distance from Czech Republic affects their choice the most are ignoring the

reference point. The Austrian Promberg is preferred by 56.3 % of subjects and French

Croisette by 43.8 %. This rate changes for country indifferent respondents who are again

acting as loss averse. The reference point influences their choice, Croisette is now preferred

by 78.7 % and the answers for Promberg represent 15.6 % of the subjects surveyed.

Table 13: Preferences of country sensitive vs. ski slope indifferent respondents, group B

Option country sensitive

respondents

Country indifferent

respondents

Promberg (X2) 18 (56.3 %) 44 (15.6 %)

Croisette (Y2) 14 (43.8 %) 222 (78.7 %)

La Combe d´Or (Y2-) 0 (0.0 %) 16 (5.7 %)

Source: Author based on survey results

55

7.4.3 Question 3

Tables 14 and 15 show the number of respondents for each option in question 3 for

questionnaire A and B. The destinations X3, Y3 are contained in both questionnaires and differ

by the distance from hotel to the ski slope. The third option represents the reference point and

differs for each questionnaire – Y3- was presented to group A and X3

- to group B.

Table 14: Answers to question 3, group A

Option Destination Number of respondents

X3 Ski resort Schladming/Dachstein Tauern, Austria

Hotel Aich-Assach, 5.6 km from ski slope

48 (14.5 %)

Y3

Ski resort Saint Gervais/Chamonix/Mont Blanc, France

Hotel Le Grand Panorama, 500 metres from ski slope

250 (75.3 %)

Y3- Ski resort Saint Gervais/Chamonix/Mont Blanc, France

Hotel Résidence de Samoens, 3 km from ski slope 34 (10.2 %)

Source: Author based on survey results

Table 15: Answers to question 3, group B

Option Destination Number of respondents

X3 Ski resort Schladming/Dachstein Tauern, Austria

Hotel Aich-Assach, 5.6 km from ski slope

114 (36.3 %)

Y3

Ski resort Saint Gervais/Chamonix/Mont Blanc, France

Hotel Le Grand Panorama, 500 metres from ski slope

196 (62.4 %)

X3- Ski slope Schladming/Dachstein Tauern, Austria

Hotel Matzling, 15 km from ski slope 4 (1.3 %)

Source: Author based on survey results

The change of preference is clear from graph 4. 75.3 % of group A subjects chose Le Grand

Panorama and 14.5 % prefer Aich-Assach. When the reference point is changed, the

preference for Le Grand Panorama is weaker, 62.4 % of group B subjects chose this resort.

Aich-Assach becomes more favourite, 36.3 % of the subjects surveyed chose it as their

preferred destination.

56

Graph 4: Answers to question 3, comparison of group A and B

Source: Author based on survey results

Table 16 shows the answers of subjects of group A. As in question 1 and 2, the subjects are

divided into two columns based on the decision weight of the factor distance from hotel to ski

slope.

Table 16: Preferences of hotel sensitive vs. hotel indifferent respondents, group A

Option Hotel sensitive respondents Hotel indifferent

respondents

Aich-Assach (X3) 9 (10.2 %) 39 (16.0 %)

Le Grand Panorama (Y3) 74 (84.1 %) 176 (72.1 %)

Samoens (Y3-) 5 (5.7 %) 29 (11.9 %)

Source: Author based on survey results

For the hotel sensitive respondents, the loss aversion effect is supported by the fact that

Le Grand Panorama is the closest hotel to ski slope. This choice was selected by 84.1 % of

hotel sensitive respondents, in comparison to 72.1 % of hotel indifferent respondents.

Table 17 shows the answers of respondents in group B. As predicted, the percentage of

subjects choosing Le Grand Panorama decreases for both hotel sensitive (to 69.7 %) as well

as hotel indifferent respondents (to 57.1 %). This change of choice is in favour of Aich-

Assach, which is now more popular because of the shift of reference point. The number of

hotel sensitive subjects who indicated Aich-Assach was their preferred choice has risen from

10.2 % in group A to 28.8 % in group B. For hotel indifferent respondents this increase is

from 16.0 % in group A to 41.8 % in group B.

14.5 %

75.3 %

10.2 % Aich-Assach

Le Grand Panorama

Résidence de Samoens

36.3 %

62.4 %

1.3 % Aich-Assach

Le Grand Panorama

Matzling

57

Table 17: Preferences of hotel sensitive vs. hotel indifferent respondents, group B

Option Hotel sensitive respondents Hotel indifferent

respondents

Aich-Assach (X3) 38 (28.8 %) 76 (41.8 %)

Le Grand Panorama (Y3) 92 (69.7 %) 104 (57.1 %)

Matzling (X3-) 2 (1.5 %) 2 (16.1 %)

Source: Author based on survey results

As seen in table 18, the country sensitive respondents prefer Le Grand Panorama (57.4 %)

over Aich-Assach (37.0 %). This rate can be caused by the characteristics of offered options.

The distance from ski slope of Austrian hotel Aich-Assach is 5.6 km, which seems

inconvenient in comparison to 500 metres from Le Grand Panorama. The comfort of having

ski slope next to accommodation can compensate the country sensitive consumer for the

trouble caused by long travel distance from Czech Republic to France. The preference of X3

could be stronger if the difference of distance from hotel to ski slope of options Y3 and X3

was smaller. For country indifferent respondents the results reflect the loss aversion

assumption. Le Grand Panorama was chosen by 78.8 % subjects and Aich-Assach by 10.1 %.

Table 18: Preferences of country sensitive vs. country indifferent respondents, group A

Option Country sensitive

respondents

Country indifferent

respondents

Aich-Assach (X3) 20 (37.0 %) 28 (10.1 %)

Le Grand Panorama (Y3) 31 (57.4 %) 219 (78.8 %)

Samoens (Y3-) 3 (5.6 %) 31 (11.2 %)

Source: Author based on survey results

58

7.4.4 Testing of Hypotheses

H1: The shift of reference point will cause a change of preference.

This hypothesis predicts different results in group A and group B for the same pair of

destinations, Xi and Yi. Placing reference point Yi- in the offer is expected to lead to a strong

preference of Yi. When a reference point Xi- is included among the options, the choice of Xi is

expected to increase. However, Xi is not expected to be preferred over Yi in absolute terms.

This fact results from the visit rate of France and Austria which was 71:29 in the last season,

in favour of France.

The hypothesis is tested by comparing the answers of subjects in group A and B. Table 19

shows the summary of results for each questionnaire. The answers to all questions are

explained in more detail in previous sections. According to a Pearson chi-square test with 1

degree of freedom, the preferences are statistically significant at the level p < 0.01.

Table 19: Comparison of preferences between Xi and Yi for group A and B

X1 Y1 X2 Y2 X3 Y3

A 39.2 % 53.3 % 33.7 % 50.3 % 14.5 % 75.3 %

B 19.7 % 68.2 % 19.7 % 75.2 % 36.3 % 62.4 %

Source: Author based on survey results

As predicted, French resorts are selected by majority in either case. Nevertheless, their

popularity decreases significantly when evaluated from the reference point Xi-, as seen in the

table. When option Xi- was part of the offer, Austrian resorts were chosen by more than 33 %

of respondents in each question. When option Yi- was offered, the same resorts were preferred

by less than 20 % of subjects in each question. For French resorts this tendency is inverse.

When the third option was the point Yi-, French resorts were preferred by at least 68 % in

each question and more than 75 % in two out of three questions. When the offer included

option Xi-, the same resorts were chosen by less than 62 % in each question and less than

53 % in two questions. The conclusion can be formulated. Change of reference point

influenced the answers of respondents and the hypothesis 1 can be therefore confirmed.

59

H2: Customers with strict preference do not act as loss averse. The loss aversion principle

has greater impact on indifferent subjects.

As described in the previous sections, each respondent had to indicate a decision weight of the

four relevant factors – price, distance from hotel to ski slope, ski slope kilometres and

distance from Czech Republic. Subjects were asked to order the factors from the most

relevant when making a decision – number 1 was assigned to this factor – to the factor that

influences the choice the least – number 4 was assigned. Hypothesis two assumes that

subjects making their decisions based on the travel distance from Czech Republic to final

destination will choose the Austrian resort, because it is the closest option. They value the

dimension distance from Czech Republic more than the other three and their indifference

curve does not match the one drafted in figures 10-12.

To test this hypothesis, the answers of country sensitive respondents to the country indifferent

ones are compared, as seen in table 20. The table shows the answers of questions that

included the option Yi-, and thus the choice of Yi was aimed for. For the country indifferent

respondents the choice of French resorts is above 70 % in each question, more than 78 % in

two questions. The country sensitive subjects indicated Yi as their preference in less than

58 % in each question, less than 51 % in two questions.

Table 20: Comparison of preferences between Xi and Yi for country sensitive and country

indifferent respondents

Source: Author based on survey results

The same principle is tested for price, hotel and ski slope sensitive versus indifferent

respondents. In table 21 the questions with option Xi- are captured. The Austrian resort is

supposed to be chosen, according to prospect theory. However, the French resorts offer the

best conditions in these three factors and thus the factor sensitive respondents are assumed not

to be influenced by the reference point. Indeed, less than 30 % of factor sensitive respondents

chose Austrian resort, whereas the preference of factor indifferent subjects is more than 41 %

in two questions and 34.6 % in the third one. A Pearson chi-square test (~1 degree of

freedom) suggests that the null hypothesis of no factor effect should be rejected at the p < .01

level. According to the results the hypothesis 2 can be confirmed.

X1 Y1 X2 Y2 X3 Y3

Country Sensitive 50.0 % 50.0 % 56.3 % 43.8 % 37.0 % 57.4 %

Country Indifferent 16.3 % 70.2 % 15.6 % 78.7 % 10.1 % 78.8 %

60

Table 21: Comparison of preferences between Xi and Yi for factor sensitive and factor

indifferent respondents

X1 Y1 X2 Y2 X3 Y3

Factor Sensitive 29.5 % 67.9 % 26.5 % 58.8 % 28.8 % 69.7 %

Factor Indifferent 47.7 % 40.3 % 34.6 % 49.3 % 41.8 % 57.1 %

Source: Author based on survey results

H3: The application of prospect theory principles in the company’s marketing will lead to the

desired improvement.

As mentioned in section 6.5., the strategy of PUXtravel is to increase the number of

customers in France. The growing tendency of the French resorts merchantability changed in

the last season when the Austrian resorts started to become more popular. The rate of French

to Austrian resorts has changed in favour of Austria from 83:17 in 2010 to 71:29

in 2011, see table 3. PUXtravel requested an improvement of this rate to the state in 2009,

75:25 for France.

Table 22 captures the results of the survey questions containing reference point Yi-. The

number of respondents choosing French resorts is compared to those subjects preferring the

Austrian option, Xi. As seen in the table, the rate France to Austria is more than 80:20 for

each question. The arithmetic mean is 82:18.

Table 22: Preference of French to Austrian resorts according to the questionnaire answers

Question 1 Question 2 Question 3

Yi 68.2% 75.2% 75.3%

Yi- 12.1% 5.1% 10.2%

Yi + Yi- 80.3% 80.3% 85.5%

Xi 19.7% 19.7% 14.5%

Source: Author based on survey results

The rate of France to Austria can be increased by simply the combination of options offered

together. When loss aversion principles are applied in an offer in favour of France, the

subjects will prefer French resorts to Austrian ones. Based on the results of the survey

analysis, the percentage of customers of France can increase of more than 10 percentage

points. The required improvement of at least four percentage points is therefore achieved and

the hypothesis can be confirmed at the level of significance p < 0.01 (Pearson chi-square test).

61

7.5 Recommendations for PUXtravel

There is one person in PUXtravel responsible for the company’s marketing. For promoting,

the agency uses low-budget outputs, primarily its own internet pages. The financial resources

of PUXtravel are limited and the company does not wish to increase marketing budget. The

application of prospect theory in PUXtravel’s marketing is recommended to be realized with

respect to the current marketing tools the company uses. No new tools are recommended in

this section, only the offer formulation and presentation that would utilize prospect theory

principles. This way the budget of the company will stay unchanged.

Based on the results of the survey, the use of a proper reference point among options would

lead to more customers for French resorts. It is suggested to formulate offers according to the

loss aversion principle and place them on the internet pages the company already uses for

promoting their services:

Homepage http://www.puxtravel.cz

Internet pages http://www.puxtravel.sk, http://www.zajazdy-lyzovanie.sk

Company’s Facebook profile with 13.000 fans http://www.facebook.com/PUXtravel

Internet pages for 15 most interesting ski resorts in France, Italy and Austria

http://www.gasteinertal.cz, http://www.risoulvars.cz, http://www.tri-

udoli.cz, http://www.kaprun-zellamsee.cz, etc.

PUXtravel cooperates with several sport shops – Subform, Trtík Sport, Sport 2000 and SNB

Zezula. Handouts with the offers could be printed out and placed in the shops.

Other marketing tools can be also used to promote the homepage where the offers would be

placed. Especially internet portals:

http://www.snow.cz

http://www.hedvabnastezka.cz, where a short reference to the offers could be

mentioned.

PUXtravel posts Public Relations articles in a student magazine Karavana and it is a partner

of VŠ league (http://www.vsliga.cz) and a general partner of Business league

(http://www.businessliga.cz). It also cooperates with VZP, the biggest health insurance

company in Czech Republic, on the project “be fit with VZP”. The travel agency offers

discount vouchers for ski tours or free tours in various events such as contents, student

parties, university balls and other student actions. A ski race PUXtravel Bílá Open is

organized.

According to the results of the survey, the right use of prospect theory principles in the

conduction of an offer would lead to the increase of customers in France of more than

5 percentage points in the next season.

62

Conclusion

This paper has investigated the possible use of prospect theory parameters in a company’s

marketing. Prospect theory has become an important tool to explain deviations from the

neoclassical paradigm of rational agents. However, the available support for prospect theory

comes almost exclusively from risky situations. This thesis addresses this gap in the literature

and presents quantitative evidence of how it can be applied to conditions of certainty.

The purpose of the thesis was to determine whether the use of prospect theory in an offer

would affect customer’s choice. The results of an experiment on microeconomic consumption

behaviour are reported. Using data of the two conducted surveys, this paper has explored the

effect of loss aversion in a hypothetical offer of a travel agency. A clear support for prospect

theory has been obtained. The subjects surveyed behaved according to prospect theory and

acted as averse to losses, violating expected utility maximization. Returning to the three

hypotheses posted at the beginning of the practical part, it is now possible to state that the

following conclusions can be drawn from the presented thesis. The results show that the

reference point is relevant to one’s decision making process. By changing the reference point,

the subjects changed their preference. The second major finding was that those subjects who

make their decisions based on a concrete attribute do not act as loss averse. The aversion to

losses that would lead to preference of a concrete option over others was observed on those

respondents who stated that decision weights of the factors in which the options differed are

approximately of the same importance to them. The results of this survey show that the use of

offers similar to those obtained in the survey questionnaires could lead to the increase of

PUXtravel’s customers in France.

These findings suggest that in general, the role of reference point and loss aversion has a

significant impact on the consumer’s behaviour. When used in a company’s marketing,

prospect theory could affect the customer’s choice. The present study confirms previous

findings about reference dependence. It contributes additional evidence that suggests the

anchoring can be influenced by external impact, not only one’s endowment or status quo. The

current findings add to a growing body of literature on using the prospect theory for

understanding and predicting consumer’s behaviour. The methods used for the travel agency

may be applied to other companies offering services or even products.

However, with a small sample size, caution must be applied, as the findings might not be

transferable to all conditions. Another important limitation that needs to be considered is the

survey method used. The results are not captured from real market place, only hypothetical

choice was made. When making an actual decision, the respondents might act differently than

stated in the questionnaire.

63

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List of tables

Table 1: Probabilities of outcomes of action A ...................................................................................... 13 Table 2: Numbers of PUXtravel customers for each country ................................................................ 44 Table 3: Proportion of clients travelling to France and Austria ............................................................. 45 Table 4: Answers to question 1, group A ............................................................................................... 49 Table 5: Answers to question 1, group B ............................................................................................... 50 Table 6: Preferences of price sensitive vs. price indifferent respondents, group A ............................... 51 Table 7: Preferences of price sensitive vs. price indifferent respondents, group B ............................... 51 Table 8: Preferences of country sensitive vs. country indifferent respondents, group B ....................... 52 Table 9: Answers to question 2, group A ............................................................................................... 52 Table 10: Answers to question 2, group B ............................................................................................. 52 Table 11: Preferences of ski slope sensitive vs. ski slope indifferent respondents, group A ................. 53 Table 12: Preferences of ski slope sensitive vs. ski slope indifferent respondents, group B ................. 54 Table 13: Preferences of country sensitive vs. ski slope indifferent respondents, group B ................... 54 Table 14: Answers to question 3, group A ............................................................................................. 55 Table 15: Answers to question 3, group B ............................................................................................. 55 Table 16: Preferences of hotel sensitive vs. hotel indifferent respondents, group A ............................. 56 Table 17: Preferences of hotel sensitive vs. hotel indifferent respondents, group B ............................. 57 Table 18: Preferences of country sensitive vs. country indifferent respondents, group A .................... 57 Table 19: Comparison of preferences between Xi and Yi for group A and B ....................................... 58 Table 20: Comparison of preferences between Xi and Yi for country sensitive and country indifferent

respondents............................................................................................................................................. 59 Table 21: Comparison of preferences between Xi and Yi for factor sensitive and factor indifferent

respondents............................................................................................................................................. 60 Table 22: Preference of French to Austrian resorts according to the questionnaire answers ................. 60

List of figures

Figure 1: Utility function of a risk averse agent..................................................................................... 16 Figure 2: Utility function of a risk seeking agent................................................................................... 16 Figure 3: Utility function of a risk neutral agent .................................................................................... 17 Figure 4: Value function ........................................................................................................................ 25 Figure 5: Probability weighting function ............................................................................................... 26 Figure 6: Indifference curves ................................................................................................................. 30 Figure 7: Multiple reference points for the choice between x and y ...................................................... 32 Figure 8: A graphic illustration of loss aversion .................................................................................... 33 Figure 9: Area of acceptance.................................................................................................................. 37 Figure 10: The illustration of options X1 and Y1 with the shift of reference point ................................ 47 Figure 11: The illustration of options X2 and Y2 with the shift of reference point ................................ 47 Figure 12: The illustration of options X3 and Y3 with the shift of reference point ................................ 47

List of graphs

Graph 1: Percentages of PUXtravel customers for each country ........................................................... 45 Graph 2: Answers to question 1, comparison of group A and B ........................................................... 50 Graph 3: Answers to question 2, comparison of group A and B ........................................................... 53 Graph 4: Answers to question 3, comparison of group A and B ........................................................... 56

72

List of abbreviations

CPT Cumulative Prospect Theory

EUT Expected Utility Theory

EV Expected Value

IC Indifference Curve

MRS Marginal rate of substitution

MU Marginal Utility

PT Prospect Theory

SQ Status Quo

TU Total Utility

List of appendices

Appendix A questionnaire A, English version

Appendix B questionnaire B, English version

Appendix C questionnaire A, Czech version

Appendix D questionnaire B, Czech version

Appendix A: Questionnaire A, English version

Preferences among ski tours

I would like to ask you to fill out the following questionnaire by checking the preferred

destination from the combination of three offered ski resorts. The results will be used for

research to my diploma thesis. .

Stated prices are for one person and include: accommodation for 7 nights, ski pass for 6 days

and transportation by bus.

1. Select the ski tour you would prefer. *For all resorts hold: medium-sized ski resort (ski slopes 100-200 km); the distance from

accommodation to ski slope to 500 metres.

Ski resort Dachstein West, Austria. Hotel Steuer. Price 11,810 Kč

Ski resort Dachstein West, Austria. Hotel Musik. Price 12,300 Kč

Ski resort Risoul/Vars, France. Hotel Foret Blanche. Price 9,580 Kč

2. Select the ski tour you would prefer.

* For all resorts hold: the distance from accommodation to ski slope to 3 km; price Kč 10,130 –

11,800.

Ski resort Dachstein West, Austria. Hotel Promberg. 130 ski slope kilometres

Ski resort Les Menuires/Trois Vallées, France. Hotel Croisette. 160 ski slope kilometres

Ski resort Pitztal, Austria. Hotel Planger. 48 ski slope kilometres

3. Select the ski tour you would prefer.

* For all resorts hold: king-sized ski resort (ski slopes more than 400 km); price Kč 10,480 – 10,860.

Ski resort Schladming/Dachstein Tauern, Austria. Hotel Aich-Assach. Distance from ski

slope 5,6 km

Ski resort Saint Gervais/Chamonix/Mont Blanc, France. Hotel Résidence et Chalets Les

Fermes de Samoens. Distance from ski slope 3 km

Ski resort Saint Gervais/Chamonix/Mont Blanc, France. Hotel Le Grand Panorama.

Distance from ski slope 500 metres

4. Please order the following factors from 1 to 4 according to how they influence

you when choosing a winter ski trip. *1= influences the most, 4= influences the least

1 2 3 4

country (distance from Czech Republic)

The distance from accommodation to ski

slope

Ski slope kilometres

Price

Gender

female

male

Your Age

Your Occupation

Appendix B: Questionnaire B, English version

Preferences of PUXtravel customers

We would like to ask you to fill out the following questionnaire by checking the preferred

destination from the combination of three offered ski resorts. The results will be used to

improve our services.

Stated prices are for one person and include: accommodation for 7 nights, ski pass for 6 days

and transportation by bus.

1. Select the ski tour you would prefer. *For all resorts hold: medium-sized ski resort (ski slopes 100-200 km); the distance from

accommodation to ski slope to 500 metres.

Ski resort Dachstein West, Austria. Hotel Steuer. Price Kč 11,810

Ski resort Risoul/Vars, France. Hotel Antares. Price Kč 11,080

Ski resort Risoul/Vars, France. Hotel Foret Blanche. Price Kč 9,580

2. Select the ski tour you would prefer.

* For all resorts hold: the distance from accommodation to ski slope to 3 km; price Kč 10,130 –

11,800.

Ski resort Dachstein West, Austria. Hotel Promberg. 130 ski slope kilometres

Ski resort Les Menuires/Trois Vallées, France. Hotel Croisette. 160 ski slope kilometres

Ski resort Les Orres, France. Hotel La Combe d´Or. 88 ski slope kilometres

3. Select the ski tour you would prefer.

* For all resorts hold: king-sized ski resort (ski slopes more than 400 km); price Kč 10,480 – 10,860.

Ski resort Schladming/Dachstein Tauern, Austria. Hotel Aich-Assach. Distance from ski

slope 5,6 km

Ski resort Schladming/Dachstein Tauern, Austria. Hotel Matzling. Distance from ski

slope 15 km

Ski resort Saint Gervais/Chamonix/Mont Blanc, France. Hotel Le Grand Panorama.

Distance from ski slope 500 metres

4. Please order the following factors from 1 to 4 according to how they influence

you when choosing a winter ski trip. *1= influences the most, 4= influences the least

1 2 3 4

country (distance from Czech Republic)

The distance from accommodation to ski

slope

Ski slope kilometres

Price

Gender

female

male

Your Age

Your Occupation

Appendix C: Questionnaire A, Czech version

Preference zákazníků cestovní kanceláře PUXtravel

Dovoluji si Vás požádat o vyplnění následujícího dotazníku zaškrtnutím svých preferencí z

kombinace nabízených lyžařských zájezdů. Výsledky použiji pro výzkum ke své diplomové

práci.

Uvedené ceny jsou za osobu a je v nich zahnuto: ubytování v hotelu na 7 nocí, skipas na 6

dní, doprava.

1. Označte zájezd, který byste preferovali. *Pro všechny nabízené možnosti platí: středně velké středisko (počet km sjezdovek 100-200 km);

vzdálenost hotelu od svahů do 500 metrů.

Středisko Dachstein West, Rakousko. Hotel Steuer. Cena 11 810 Kč

Středisko Dachstein West, Rakousko. Hotel Musik. Cena 12 300 Kč

Středisko Risoul/Vars, Francie. Hotel Foret Blanche. Cena 9 580 Kč

2. Označte zájezd, který byste preferovali.

*Pro všechny nabízené možnosti platí: vzdálenost hotelu od svahů- 3 km; cena 10 130 – 11 800 Kč.

Středisko Dachstein West, Rakousko. Hotel Promberg. Sjezdovky 130 km

Středisko Les Menuires/ Tří Údolí, Francie. Hotel Croisette. Sjezdovky 160 km

Středisko Pitztal, Rakousko. Hotel Planger. Sjezdovky 48 km

3. Označte zájezd, který byste preferovali.

*Pro všechny nabízené možnosti platí: obří středisko (nad 400 km sjezdovek); cena 10 480 -

10 860 Kč.

Středisko Schladming/Dachstein Tauern, Rakousko. Hotel Aich-Assach. Vzdálenost od

svahů 5,6 km

Středisko Saint Gervais/Chamonix/Mont Blanc, Francie. Hotel Résidence et Chalets Les

Fermes de Samoens. Vzdálenost od svahů 3 km

Středisko Saint Gervais/Chamonix/Mont Blanc, Francie. Hotel Le Grand Panorama.

Vzdálenost od svahů 500 metrů

4. Seřaďte uvedené faktory od 1 do 4 podle toho, jak Vás ovlivňují při výběru

lyžařské dovolené. *1= nejvíc ovlivňuje, 4= nejmíň ovlivňuje

1 2 3 4

země (vzdálenost z ČR)

vzdálenost svahů od hotelu

počet km sjezdovek

cena

Vaše Pohlaví

žena

muž

Váš Věk

Vaše Zaměstnání

Appendix D: Questionnaire B, Czech version

Preference zákazníků cestovní kanceláře PUXtravel

Dovolujeme si Vás požádat o vyplnění následujícího dotazníku zaškrtnutím svých preferencí

z kombinace nabízených lyžařských zájezdů. Výsledky použijeme pro zkvalitnění námi

poskytovaných služeb.

Uvedené ceny jsou za osobu a je v nich zahnuto: ubytování v hotelu na 7 nocí, skipas na 6

dní, doprava.

1. Označte zájezd, který byste preferovali. *Pro všechny nabízené možnosti platí: středně velké středisko (počet km sjezdovek 100-200 km);

vzdálenost hotelu od svahů do 500 metrů.

Středisko Dachstein West, Rakousko. Hotel Steuer. Cena 11 810 Kč

Středisko Risoul/Vars, Francie. Hotel Antares. Cena 11 080 Kč

Středisko Risoul/Vars, Francie. Hotel Foret Blanche. Cena 9 580 Kč

2. Označte zájezd, který byste preferovali.

*Pro všechny nabízené možnosti platí: vzdálenost hotelu od svahů- 3 km; cena 10 130 – 11 800 Kč.

Středisko Dachstein West, Rakousko. Hotel Promberg. Sjezdovky 130 km

Středisko Les Menuires/ Tří Údolí, Francie. Hotel Croisette. Sjezdovky 160 km

Středisko Les Orres, Francie. Hotel La Combe d´Or. Sjezdovky 88 km

3. Označte zájezd, který byste preferovali.

*Pro všechny nabízené možnosti platí: obří středisko (nad 400 km sjezdovek); cena 10 480 -

10 860 Kč.

Středisko Schladming/Dachstein Tauern, Rakousko. Hotel Aich-Assach. Vzdálenost od

svahů 5,6 km

Středisko Schladming/Dachstein Tauern, Rakousko. Hotel Matzling. Vzdálenost od

svahů 15 km

Středisko Saint Gervais/Chamonix/Mont Blanc, Francie. Hotel Le Grand Panorama.

Vzdálenost od svahů 500 metrů

4. Seřaďte uvedené faktory od 1 do 4 podle toho, jak Vás ovlivňují při výběru

lyžařské dovolené. *1= nejvíc ovlivňuje, 4= nejmíň ovlivňuje

1 2 3 4

země (vzdálenost z ČR)

vzdálenost svahů od hotelu

počet km sjezdovek

cena

Vaše Pohlaví

žena

muž

Váš Věk

Vaše Zaměstnání