An Empirical Investigation of Factors Affecting the Standardization of Service Pricing:

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A Case Study of Flexlink

Louise Lorentzon & Oscar Johnsson2013-05-23

AbstractOver the last decades, the service sector has increased as a percentage of the economies. This paper analyzes whether service prices can be internationally standardized based on the Purchasing Power Parity (PPP) theory. The findings confirm that the services’ unique features intangibility, inseparability, heterogeneity and perishability (IIHP) complicate standardization, for an international price comparison to be possible. From our models, there is no statistical proof that exchange rate, as the sole price adjustor in PPP, has an effect on pricing. We conclude that there are macro factors in the models, not covered by the PPP theory that acts against an implementation of standardized prices. From the study on Flexlink, a company that assembles and installs transporter systems, it was verified that the sales units regularly use price discrimination, as a result of the markets’ high price elasticity, an adaption to the local markets are necessary in order to be competitive.

Keywords: Pricing, Services, PPP, IIHP, FTU, International trade, Wage, Cost of Living

Spring 2013

Supervisor: Martin Holmén

Bachelor Thesis in Corporate Finance (15 hp)

The Department of Economics at the School of Business, Economics and Law

Oscar Johnsson 19900606-0231, Louise Lorentzon 19890518-0140

Acknowledgements

We would like to thank our supervisor Martin Holmén for sharing his knowledge, and for helping us with the issues that arose during the writing of this thesis. We would like to thank Carina Karlsson, Magnus Andersson and Kristina Wall Jungbjer for assisting us within each of their area of professional expertise.

We would also like to give thanks to all the Finance Managers who participated in the interviews.

And finally, we would like to thank Hilda, who entertained and inspired us during our long working days.

________________________ __________________________ Oscar Johnsson Louise Lorentzon

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ACKNOWLEDGEMENTS 2

1. INTRODUCTION AND PROBLEM STATEMENT 5

1.1. Background 5

1.2 Research Questions 7

1.3 Methodology and Delimitations 71.3.1 Literature Review 81.3.2 Survey 81.3.3 Regressions 8Fig.1 Essay Process: The Figure Shows the Main Structure of the Thesis. 9

2. FLEXLINK’S HISTORY 9

3. DEFINITION AND FRAMEWORK 10

3.1 Definition - Service 113.1.1 Intangibility 123.1.2 Heterogeneity 133.1.3 Inseparability 143.1.4 Perishability 14

3.2 FTU Framework 153.2.1 Facilities 163.2.2 Transformation 163.2.3 Usage 17

4. THEORY 18

4.1 Purchasing Power Parity (PPP) 184.1.1 Definition 184.1.2 Law of One Price 194.1.3 The Development of the PPP 194.1.4 Critiques of the Applied PPP 20

5. METHODOLOGY 22

5.1 Macro Variables on Pricing 225.1.1 Dependent Variables 225.2.3 Independent Variables 23

5.3 The Regression Model 27

5.4 Hypothesis 28

6. EMPIRICAL RESULTS 29

6.1 Correlation Results 29

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6.2 Regression Results 31

6.3 Analysis of Regressions 346.3.1 Cost of Living Models 346.2.2 Cost of Engineer Models 356.2.3 Cost of Fitters Models 36

6.3 Survey Results 37

6.4 Analysis Survey 39

7. DISCUSSION 40

8. CONCLUSIONS 42

9. LIMITATIONS AND SUGGESTIONS 44

BIBLIOGRAPHY 46

Literature and Articles 46

Websites 49

Interviews and Observations 51

APPENDIX 52

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Definitions

AGRI_% Percentage of the population working in the agriculture sector

UNEMP_% Percentage of the population unemployed

BMI_PPP Big Mac index – Purchasing Power Parity adjusted

GDP/CAP The GDP/ Capita in Dollar

GDP_DEF The GDP Deflator

COL_IN Cost of Living index, with USA as base country

EX_RATE Exchange rate, with SEK as base currency

POVU_2_% Percentage of the population earning less than 2 dollars/day

SERV_% Service sectors percentage part of the GDP

AV_WAGE Average wage/hour

PPP Purchasing Power Parity

IIHP Intangibility, inseparability, heterogeneity and perishability

FTU Facilities, transformations and usage

OECD Organization for Economic Co-operation and Development

ENG_COST Average Engineer cost/hour at Flexlink

FIT_COST Average Fitter cost/hour at Flexlink

GDP Gross Domestic Product

CPI Consumer Price Index

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1. INTRODUCTION AND PROBLEM STATEMENT 1.1. Background

Organizations that pursue business globally, are participating in several markets. If a

customer has affiliates in more than one country that require services, prices should be

internationally standardized to accommodate the trade. International firms want to

charge the same price to the same customer in different countries; otherwise, the same

customer will have different costs for different countries that will incur problems.

Based on these conditions, standardized prices ought to be the norm, but there are

several factors that complicate the standardization of service performance and price.

Service pricing is becoming an increasingly important topic for multinational

corporations, as there have been a shift from products to services in developed

countries. Cassel (1918) presented the Purchasing Power Parity (PPP) theory, based

on the principle of equal purchasing power in all countries after adjusting for

exchange rate. The PPP theory by Cassel (1918), as well as Taylor and Taylor (2004)

and Rogoff’s (1996) take on the theory, provide the framework for this thesis

concerning international standardization of service pricing. A company’s main

objective is to maximize profit by using the best strategy. Based on the theory by

McCarthy (1960) there are 4 P’s; product, price, place and promotion, all of which are

costs except for price. To set the right price is of utmost importance since a too high

price might make the firm non-competitive, while a too low price can create losses.

Furthermore, existing theories and literature mainly consider pricing of products, and

there is an absence of thorough studies on services.

This paper will discuss the subject from an economic and management view. Starting

from a macro level with empirical results, there will be three cases examined; a

general for the world, for fitters and for engineers. The service professions differ in

terms of difficulty; fitters assemble the systems, while engineers design and act as

project leaders. The macro factors applied are recognized as good indicators for

pricing. At a micro level, a case study of Flexlink, a company that assembles and

installs transporter systems.

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Current research and literature is vague and ambiguous regarding the difference of

goods and services, and therefore there is an attempt to define a service and the

specific characteristics. The aim of this thesis is to examine whether service prices can

be internationally standardized. According to the PPP theory there should be global

price parity, and if violated it provides evidence against internationally standardized

service prices.

The case study will be conducted on Flexlink; a global company, headquartered in

Gothenburg, that assembles and installs transporter systems. Their revenue is based on

selling projects that include the product and service. The regression analysis will be

based on Flexlink’s cost of services since they have reported differences among their

19 sales units, and in-depth interviews will be conducted. The case study will

favourably confirm the findings on a global level.

Pricing theory is a complex subject due to the many aspects involved when setting the

price, but by a multifaceted approach the aim is to give a comprehensive assessment.

The different perspectives presented in this paper are an attempt to contribute to price

theory, with a focus on services; from a macro to a micro point of view.

1.2 Research Questions

(i) Can service prices be standardized based on economic theories or should an

adaption be made to the local market?

(i.i) Do macro factors affect the pricing of services such that standardized

pricing is not feasible?

(ii) Can the Flexlink findings strengthen the Purchasing Power Parity for service

pricing?

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1.3 Methodology and Delimitations

The thesis has two approaches:

Macro: Examined through literature and empirically.

Micro: Case study; survey results to strengthen the findings.

The assessment of the perspectives will be carried out by using a survey, regression

and an analysis of the literature.

1.3.1 Literature ReviewIn order to answer the research questions, the characteristics of a service need to be

separated from the goods. First the service is discussed with the traditional IIHP

(Intangibility, heterogeneity, perishability and inseparability), a model promoted by

Lovelock (1999), Bowen and Schneider (1988), Gummesson (2004), Berry (1980),

Beaven and Scotti (1990). From critiques of the IIHP, the more recent FTU Framework

is introduced with a process based approach (Moeller, 2008; Fließ and Kleinaltenkamp,

2004; Vargo, 2008). However, both models can be seen as simplifications, but are

necessary in order to identify the service characteristics.

The thesis main theory is the Purchasing Power Parity (PPP) that supports the

standardization of service pricing, if price parity exists (Cassel, 1922; Taylor and

Taylor, 2004). The theory is a valuable tool for explaining pricing, but has been

criticized to not hold in a globalized world.

1.3.2 SurveyThe survey is based on interviews with the Finance Managers in 7 out of 19 countries

where Flexlink have sales units. Due to the short time window for the survey

interviews, all countries could not participate. The questions are divided into two parts;

internal customers are defined as in-house trade between Flexlink’s sales units, and all

other trade is with external customers, non-Flexlink. The dividing of questions into two

parts (Appendix), was done after input from the Flexlink supervisors to make it easier

for the sales units to give correct answers. There are a total of 31 questions, both

multiple-choice and full-answer. The Finance Managers provide an updated and reality

based view of service pricing and the questions cover topics from macro, micro to

accounting (Appendix).

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1.3.3 RegressionsIn the regression tests, panel data is used. The data is collected for the years 2001-

2011. In the world regressions, the dependent variable is Cost of Living, and in the

Flexlink regressions, the dependent variables are Cost of Engineers and Cost of Fitters.

The independent variables are: Big Mac Index, Agriculture, Poverty limit $2,

unemployment, GDP/Capita, GDP Deflator, Exchange rate, average wage/hour and

percentage employed in the service sector. Below are the countries where the nineteen

sales units are located:

Europe Belgium France* Germany Hungary* ItalyPoland* Spain* Sweden* United Kingdom Russian

Asia and the Pacific Australia* China India Indonesia Malaysia* SingaporeNorth and South America Brazil Canada United States

*) The countries chosen for personal interviews

Fig.1 Essay Process: The Figure Shows the Main Structure of the Thesis.

The process of the essay starts from an Informatory point of view, where the authors’ describe and

investigate the problems, limitations and main approaches. Thereafter, the essay’s perspective is an

Exploratory view and focus is on relevant literature. After that, an Empirical aspect is applied to

analyse the regressions and survey results in order to answer the research questions. Finally, the

findings are analysed and evaluated in order to confirm the results.

Informatory Exploratory Empirically Analysis Confirmatory

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1988–03 Establishment of Sales Units in: Japan, USA, Germany, Singapore, Brazil, France, Italy, UK, the Netherlands, Australia, Czech Republic, China, Poland, Hungary, Spain, Malaysia, Thailand, Finland. The first information/co-ordination system was introduced

2. Flexlink’s History

Timeline

Flexlink is a manufacturing based company of conveyor system; the procedures are loading,

processing, assembly and packaging. In 1980, Flexlink was founded as a spin-off company

from the roller ball bearing maker SKF (Svenska Kullagerfabriken AB). The international

success came immediately, and the Flexlink conveyor systems quickly got recognition in a

wide range of industries (Flexlink 2013). At present, Flexlink is one of the main players in the

segment material handling systems, and has established Sales Units in 19 countries and

partner companies in over 50 countries (Flexlink information PPT 2013). The historical

timeline is based on Flexlink’s documents (2013) and Flexlink’s informational PowerPoint

(2013).

1980

1980 Flexlink was founded in Gothenburg, as an efficiency project within SKF

1982-87 Development of the organization and product solutions

1997 Flexlink was aquired by EQT and became an independent company for the first time

2011 January 11TH FlexLink was acquired by COESIA GROUP, and became a member of the innovation based industrial group from Bologna, Italy.

2012 Flexlink is one of the largest specialized conveyor distributers in the world with revenues of 1,6 billons SEK

2010 Acquistions of the Automation Division from Schüco, Germany, and Italian e-cube.

2013

2005 Acquired by ABN Amro Capital, now AAC Capita

2006 Acquisition of Tops Conveyors, a company based in Canada

2007 Opening of sales companies in India and Indonesia

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3. DEFINITION AND FRAMEWORK

3.1 Definition - Service

During the past 20-30 years, there has been a dramatic increase in the service sector.

According to Edvardsson et al. (2000), different services in the private as well as in

the public sector account for about 70-75 % of the gross national product in most

OECD-countries. He also argues that services are gaining in importance and are

gradually becoming an essential part in all types of commodity manufacturing firms;

many firms even define themselves as service oriented rather than engineering

oriented. Nowadays, it is a common understanding among most service researchers

that in a world characterized by turbulence (Mintzberg, 1993), services are becoming

an outstanding tool both to differentiate the business (Oliva & Kallenberg, 2003) and

to develop sustainable competitive advantage (Barney, 1991).

It has been debated, for instance by Matanovich (2003), that there should be no

difference between pricing of goods and services. He emphasizes the importance of

focusing on how much value that is offered to the buyer rather than focusing on if it is

a good or a service. However, there is more evidence proving that key differences

exist between the pricing of goods and services, and this will be our view for this

thesis.

Lovelock (1999) argued that the rather intricate nature of the service sector has

created a complex problem regarding the definition of a service. Not only have

services gained importance in the developed world, but what is perceived as a service

has also changed due to technology (Rust, 2004). The out-dated but still general view

is that services are based on personal contact (Bowen, 2000), but many services are

nowadays net-based e.g. personal banking, lectures, shopping. In order for the term

“service” to be defined correctly, new traits and sectors of application must be added

to make it current (Moeller, 2010).

Lovelock(1999) argues that it is the performance/delivery of the service that makes it

so hard to grasp, and the fact that services are quite abstract. To most people, he

argues that to understand the manufacturing businesses is much simpler. You can

easily understand the process of assembly, transformation or creation of goods, by

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using physical input to get physical output in for example a factory. To understand or

define what type of value, or how much a service really matters is much harder

according to Lovelock (1999).

From findings in the work of other researchers there is a wide range of methods in

order to distinguish goods from services. Given the examined research material, two

approaches will be discussed. Firstly, the characteristics of a service are condensed

into four main groups, IHIP; Intangibility, heterogeneity, perishability and

inseparability (Lovelock, 1999), (Hansen & Mowen, 2006), (Barney 1991), (Flipo

1988) followed by a more modern approach, the FTU Framework (Moeller, 2008).

Fig. 3 - IHIP Characteristics (Explained below)

3.1.1 IntangibilityThe intangibility aspect is always connected to services and has for long been

considered as the most fundamental characteristic (Bowen and Schneider, 1988). The

intangible side described; cited Berry (1980, p.24) “A good is an object, a device, a

thing; a service is a deed, a performance, an effort”. The intangible side of a service is

subject to its immateriality and the very problem when it comes to describing what a

service stands for, and the valuation of the performance. This problem is not new,

back in the 16th century; Smith (1776) felt that services were non-value adding and

only goods that could be included in trade would create wealth for the country. Say

(1836) considered Smith to be wrong and argued that even though services are not

Intangibility Hetrogeneity

Perishability Inseparability

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material, their usefulness and surrounding activities create value. The difficulty of

selling a service is that what is being sold is a contract of an immaterial performance

(Bowen and Schneider, 1988). What the buyer actually receives and the quality of the

service is vague which causes uncertainty regarding the value (Shostack, 1977).

There is criticism of the intangible aspect of a service. In order to perform a service,

tangible goods are normally required (Shostack, 1977). An obvious situation is a

barber performing a haircut, perceived as an intangible service. For the service to be

executed there are a need for a studio, scissors, hairdryer which are tangible. A service

performed on a person who is tangible (haircut), will result in a change due to the

service and is therefore tangible (Moeller, 2010). Much focus has been placed on the

transformation process of resources given by the customers' input, which also can be

interpreted as the services’ main purpose (Hill, 1977). For most goods input is not

given by the customers for transformation and only the finished product is sold.

However, there are grey areas in terms of customized goods, when the customer asks

the seller to perform a service that results in a product (Moeller, 2010).

3.1.2 Heterogeneity One of the difficulties regarding services is for the outcome to be the same, and thus

to standardize a service is hard (Edgett an Parkinson, 1993). Different factors that are

considered to be making the service heterogeneous have been investigated with

separate viewpoints. Beaven and Scotti (1990) suggested that it was the outcome that

differed and thus the services’ results cannot be considered homogeneous. According

to Lovelock and Gummesson (2004) it also depends on how the service is performed

and that this creates a heterogeneous situation. The same service’s quality can vary a

lot depending on who performs it and the daily status of that person. It does not only

depend on the service provider for the service to be heterogenic, the customer

expectation and participation plays an important role in the service outcome (Palmer

and Cole, 1995).

Not everyone agrees that services cannot be homogeneous, it depends on the nature of

the service and some may therefore be standardized (Lovelock and Gummesson,

2004). According to Moeller (2010), some services can be standardized by using the

same process, while others such as customized services cannot be made by following

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the same model. There are discussions concerning whether it is the service that

actually varies, but according to Vargo and Lusch (2004) the variations are due to the

human error, which can be reduced but not avoided. The technology has become more

advanced over the past centuries, and services previously handled over the counter

have become computer-based, e.g. banking and shopping (Furrer, 2003). The result of

this is that more services can be standardized and variations will decrease according to

Lovelock (1983). The input to the service provided by the customer will vary, and

therefore the amount of time and the execution might differ but this is not due to the

service offered (Lovelock, 1983, p.16).

3.1.3 Inseparability Inseparability comes from the fact that the production and consumption of a service

takes place at the same time, making it impossible to divide the two (Say, 1836).

Berry (1980, p.259) argues that this is due to the fact that the customer and the person

performing the service cannot be separated and both must be in the same place at the

same time. From this follows that the relationship between the provider and customer

plays an important role for the perceived service experience and overall impression

(Bitner, 1990). Other differences between services and goods have also been

described, such as the order of the sales process; the service is sold in terms of an

agreement, and then the service is produced and consumed at the same time.

Lovelock and Gummesson (2004, p.29) found that there are many services provided in

today's society where the customer is not present at the process of the service. They

gave examples of transport companies carrying goods, but when the customer receives

the packet the service is already completed. However, Lovelock (1983) argues that

services are sometimes characterized by inseparability but this depends on the service

being performed. He chooses to split up the services into two groups, the physical

body and physical belongings. The former must be present at the execution of the

service but regarding the latter, the customer does not need to be present.

3.1.4 Perishability This is one of the things that distinguish services from goods; they disappear while

they are consumed. It is one of the main opinions regarding why services are difficult

to analyse, the fact that the service cannot be kept or stored (Beaven and Scotti, 1990;

Kotler, 1994). Smith (1776, p. 351) was straight to the point on perishability “the

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labour of the mental servant, on the contrary, does not fix or realize itself in any

particular subject or vendible commodity. His services perish in the very instant of

their performance”.

The criticism of perishability is directed against the fact that services are available in

computer systems, knowledge and people (Gummesson, 2004, p.124). Services are

also preserved in the form of receipts showing the performed action (Edvardsson et

al., 2005). Lovelock (2000) argues that services are different and some has a time-

limit while others continue to give value to the customer. The perishable aspect is not

unique for services; many goods disappear after consumption e.g. food. From some

services, value remains after consumption and therefore what is left behind is a proof

that services do not always completely perish. This is very obvious regarding

education, the service performed by the professor of teaching the students, will remain

as knowledge (Hill, 1977). It is hard to adapt services to the economic cycles since

services cannot be stored and are entirely based on customers’ demand when using a

facility (Ng et al., 1999).

3.2 FTU Framework

It is not an optimal approach to describe what differentiates a service from a product

by using the four IHIP characteristics (Lovelock and Gummesson, 2004, p.32). The

reason is that society has changed and today the research focuses on other kinds of

services, and not only the personal based services that were more occurring in the past

(Bowen, 2000). The IHIP characteristics are seen as valuable parameters to describe a

service (Edvardsson et al, 2005), but there is a need for adaption to better fit today's

society. The problem according to Moeller (2010) is that the implementation of IHIP

characteristics is vague, and that the different characteristics need a new interpretation

of what part and stage of the service is described. To do this, Moeller (2008) argues

that services should be divided into different stages and thus get the four IHIP

characteristics to work better as helping tools to define a service. One way to do this is

to use the FTU framework that describes a service in three process parts facilities,

transformation and usage.

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Fig. 4 FTU Framework; IHIP Characteristics

3.2.1 FacilitiesFacilities enable the service performance and are the value-required input in the

processes (Moeller, 2010). Facilities are usually a workplace where the service can be

performed, machines and equipment, and staff with knowledge (Shostack, 1992).

Edvardsson et al. (2000) phrased it that these are essentials for a service to take place.

Under these conditions the facilities consist of both tangible and intangible assets and

it is clear that a service cannot completely be associated with intangibility. Facilities

are only the input for the service to be performed, without customers, the assets

remain unused (Fließ and Kleinaltenkamp, 2004) as opposed to goods that can be

produced and stored.

According to Moeller (2010) perishability is a characteristic of facilities since the

competence (personnel and equipment) provided, must be supported by a customer’s

input of resources, in order to be activated and not perish as seen from the provider’s

point of view. Heterogeneity is also a part of the facilities regarding what the

customers provide, their input will vary and so the prerequisites are not homogenous

(Moeller, 2010).

3.2.2 Transformation The service that is sold is a promise of a change to fix or improve (Hill, 1977).

Depending on which resources are used, these can be divided into direct and indirect

service provisions (Moeller, 2008). First, indirect service provision is when the

PerishabilityHeterogeneity

Facilities

IntangibilityInseparability

TransformationValue-creation

Usage

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provider arrange for the input to the service in the case of goods. Regarding the direct

service provision is when it is the customer who provides input to the service, and

what we traditionally call a service. In the latter case the limitation of the provider is

that the customer is owner to part of the resources necessary for the service that

cannot be accessed otherwise (Hill, 1977). The resource can be the client's body e.g.

surgery or an asset like car reparation or knowledge-based banking services etc. (Fließ

and Kleinaltenkamp, 2004). The customers contribute their resources because of the

need for expertise, along with the providers assets a transformation can be achieved

(Moeller, 2010). Vargo (2008) argues that there are two ways in which the provider

interacts with the customer; coproduction is when the two work together to create the

transformation, and co-creation of value is when synergies create added value to both

parties.

In the transformation part what the provider sells to the customer is an agreement of a

service and not a tangible product. The intangibility aspect is therefore a part of the

transformation stage (Moeller, 2010). In order for the service to be performed in the

transformation stage, the customer’s resources needs to be present and are therefore

inseparable from this stage (Moeller, 2010).

3.2.3 UsageThe usage of the transformed service is the last step in the FTU framework (Fließ and

Kleinaltenkamp, 2004). In order to create value the customer needs to use the service

to benefit from the improvement (Moeller, 2010). The provided service that is now

used can either be standardized based on a template from a catalogue or customized to

fit the customer's unique needs (Fließ and Kleinaltenkamp, 2004).

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4. THEORY 4.1 Purchasing Power Parity (PPP)The Purchasing Power Parity (hereafter PPP) has been chosen as main theory for this

thesis, and all discussions will be based on either PPP or the macro factors examined in

the next part of the paper. The PPP theory’s assumptions are valuable in order to

connect the literature and previous findings, and answer the first research question

“Can service prices be standardized based on economic theories or should an adaption

be made to the local market?”.

This part of the thesis will examine and describe the PPP theory, evaluate other

researchers’ findings, and provide the reader knowledge of the theory’s limitations.

Factors in the economy affecting the PPP are described below.

4.1.1 DefinitionThe Swedish economist Gustav Cassel named the theory and stated:

“Our willingness to pay a certain price for foreign money must

ultimately and essentially be due to the fact that this money possesses a

purchasing power as against commodities and services in that country.

On the other hand, when we offer so and so much of our own money,

we are actually offering a purchasing power as against commodities

and services in our own country. Our valuation of a foreign currency

in terms of our own, therefore, mainly depends on the relative

purchasing power of the two currencies in their respective countries.”

Gustav Cassel, economist (1922, pp. 138-39)

The Purchasing Power Parity is an astonishingly simple theory that states that the

nominal exchange rate between country A and B must be equal to the purchasing ratio

of the price levels between country A and B; implying that one unit of the specific

currency in country A has the same purchasing power in a foreign country, country B

(Taylor and Taylor 2004). First and foremost, the idea behind the PPP is that one unit

of country A’s currency should buy the same mix of goods in country A, as equivalent

amount units of country B’s currency should be able to buy in country B. That means

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that Country A and B have the same Purchasing Power, at the current exchange rate.

(Taylor and Taylor, 2004)

4.1.2 Law of One Price The PPP theory was developed from the Law of One Price; but a common mistake is

to equate the PPP and the Law of One Price (LOP), but in fact there are significant

differences between the two. The LOP is based on the theory of international

arbitrage. The LOP states that when the price of internationally traded goods are

converted to a common currency, the goods should have the same price in different

countries. However, there are some assumptions behind the LOP theory that has been

questioned. For example LOP assumes that there is perfect competition in the market,

no trading barriers or tariffs, and no transportation costs. In reality, due to the

existence of transportations cost as well as trading barriers and tariffs, the prices vary

between different countries and the LOP assumptions are questionable (Froot and

Rogoff, 1995; Rogoff, 1996).

4.1.3 The Development of the PPP The Purchasing Power Parity theory has a long and well-debated history that can be

can be dated all the way back to the 16th century, Spain, Europe. During the 19th

century, well-known economists like Ricardo, Marshall, Mill, Goschen et al, tested

and developed comparable PPP landscapes (Rogoff, 1996). The theory first got its

name back in 1918 by Cassel. Cassel’s ideas about the PPP were developed in a

backwash of the World War I and the big collapse of the modern financial system.

Before the Great War, all countries followed the global gold standard; the currencies

were bound to gold, and could be converted to gold at fixed prices. This created an

exchange rate between countries, which reflected the relative price of gold. After the

war started it became quite difficult to maintain the gold standard system, and

speculators feared that the countries would devalue their currencies to gain short-term

revenues. The gold standard system was abandoned, and many countries let the

exchange rate float, or bound it to the dollar (Rogoff, 1996). In this turbulent era,

Cassel argued for the accuracy and usage of the PPP theory to explain why the

exchange rates should depend on the compared purchasing power between countries.

Since then, the idea of PPP has been discussed and debated in an abundance of

reviews and papers among economic researchers all around the globe (Rogoff, 1996).

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4.1.4 Critiques of the Applied PPP There have been several attempts to prove or undermine the theory, and there are

arguments both for and against PPP.

There is an easy way to check whether there are deviations from the Purchasing Power

Parity, by comparing the difference in price of one McDonald´s Big Mac hamburger

around the globe. Named by the hamburger, the Big Mac Index is semi-annually

published by the newspaper “The Economist”. The main purpose of the index is to

compare prices in a common currency (dollar), to analyse the price differences. The

index effectively measures if a currency is over- or undervalued compared to the

USD. The assessment is built on the assumption that the currency would be correctly

valued, if the international prices of burgers were equivalent dollars (Rogoff, 1996).

This kind of analysis has limitations, and Taylor and Taylor (2004) argued that the

approach is a simplification of reality and therefore should not hold. Nevertheless,

despite the imitation mentioned, The Big Mac index has been very popular and

therefore the Economist created another index describing the price of a tall cup of

coffee at Starbucks (The Economist 2013).

The Big Mac- and the Starbucks index are both engaging ways to visualize the

exchange rate’s function. Taylor and Taylor (2004) argued that there are several

legitimate reasons why the price of a Big Mac or a Starbucks coffee might differ

between countries that cannot be explained by the exchange rate. The primary reason

is the fact that the economic environment is not perfect (Taylor and Taylor, 2004).

Reasons for international price differences:

Not easily traded internationally

Local subjective estimation of the services’ complexity factor affect wages

Local differences in price level affect costs

None of the factors above are conveniently arbitraged in the international market, and

most of the arguments around the PPP are based on the assumption that there are wide

international arbitraging. Hence, this indicates that the Big Mac index should be

treated with caution when interpreting results (Taylor and Taylor 2004).

20

As mentioned above, in theory the PPP assumptions should hold when comparing to

the “Law of One Price”, but the reality is more complex. If the price of a product

differs in different regions, a person could make a totally riskless profit by shipping

the good from area A, where the price of the good is low, to area B where the price is

relatively higher. This statement ignores the fact that there are transaction costs in the

market, which hinder the good from being moved from A to B and lower the price.

Furthermore, one of the PPP theory’s limitations is the definition of the market basket

in order to compare goods internationally. The taste and preference of goods between

countries differ, and it is therefore not accurate to use the same basket for every

country. Regardless of the preferences, there are also difficulties in purchasing exactly

the same goods in different countries due to availability. However, if there was an

accurate market basket of traded goods, in a perfect market without transaction costs,

the Law of One Price would imply that the PPP theory of an adjusted exchange rate

should hold (Rogoff, 1996). As mentioned, there are strong objections why the

relationship between the LOP and PPP cannot hold. Different transaction costs

disaffirm the theory; e.g. transportation cost, trading barriers, tariffs, taxes etc. (Engel

and Rogers 1996).

Further, there are goods that are not traded between all countries in the world;

consequently the weights of those goods are not going to be equal in the countries’

market baskets. Moreover, observations have also shown that countries tend to create

differentiated goods instead of substitutes. Some of these problems, however, could be

addressed by using more accurate statistic data (Engel, 1996).

Taylor and Taylor (2004) argue that since the PPP is based on the traded goods, a more

appropriate test is the PPI (producer price indices) in comparison to the CPI (consumer

price indices). Taylor and Taylor (2004) claim that the PPI usually reflect the

tradeable manufacturing goods, while the CPI tends to reflect more non-tradeable

goods. By using PPI, the analysis would be more accurate according to Taylor and

Taylor (2004).

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In this thesis the aim is to test whether the Purchasing Power Parity holds for services

internationally, or if it is too simplified and the problems mentioned above are actual

issues.

5. Methodology

In the regression tests, panel data is used. The regressions are run with data for macro

variables clustered by country. The country clusters are independent, but the factors

contained in the cluster are dependent. In the regressions, Huber (1967) –White (1980),

standard errors are used to adjust for clusters. xtreg matches the regression models to

the panel data for both random and fixed effect. The Cost of Living data is unbalanced,

since each country is not observed every year. The Engineer and Fitter data is

balanced, since each country is observed every year.

The data is collected for the years 2001-2011. Accounting data, economic data and

exchange rate data are collected from Thomson’s DataStream. The Cost of Living

index is collected from U.S. Department of State, and the Big Mac Index is retrieved

from The Economist. Agriculture data, unemployment data and poverty $ 2 are

collected from World Bank. The Cost for Fitters and Engineers are collected from

Flexlink’s financial statement. In the world (general measure) regression the

dependent variable is Cost of Living, tested for 9 macro-variables in 7 models. The

sample consists of 188 countries and the number of years is 1880. For the regression

based on Flexlink’s cost of Fitters and Engineers as dependent variables, the tested

macro- variables are 9 in 7 models for Fitters, and 9 in 5 models for Engineers. The

sample consists of 19 Flexlink Sales Units and the number of years is 190.

5.1 Macro Variables on Pricing

In order to investigate the macro factors that have an impact on service pricing, the

variables are first discussed below. The variables are seen as representative of the

macro- and micro economic factors. There are two types of variables examined;

Dependent and Independent.

5.1.1 Dependent VariablesThe dependent variables examined are Cost of Living Index and the hour rate for

Fitters/Engineers at Flexlink.

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5.1.1.1 Cost of Living Index (COL_IN)The Cost of Living Index has Washington DC as base (Washington DC=100). The

index compares the costs in Dollars ($) of buying representative goods and services

(excluding education and housing) in foreign countries with the cost of equivalent

goods in the DC area. The index excludes all kind of extravagant goods and services,

and is based on the average American consumption behaviour. The Cost of Living

Index has limitations in measuring and comparing costs differences between countries.

The Index focuses on the comparison of American families and has DC=100 every

year, which makes it impossible to use it for measuring cost changes over time in a

foreign country. The Cost of Living Index is used in this thesis to examine if there are

any differences between countries and if there are any similarities between Cost of

Living and Cost of Engineers and Cost of Fitters at Flexlink (U.S. Department of State

2011).

5.1.2.2 Cost of Engineer The Cost of Engineer is the average hourly rate for an Engineer at Flexlink, in 19

different locations around the globe. The variable includes Sales and Administrations

costs, wages, rents, and social expenses etc.

5.1.2.3 Cost of FitterThe Cost of Fitter is the average hourly rate for a Fitter at Flexlink, in 19 different

locations around the globe. The variable includes Sales and Administrations costs,

wages, rents, and social expenses etc.

5.2.3 Independent Variables

5.2.3.1 The Big Mac IndexThe Big Mac Index (BMI) was created in 1986 by the magazine The Economist. The

index is based on the idea that the exchange rates are reflected in the price levels,

when two countries are compared, known as the Purchasing Power Parity (PPP)

(Clements, Lan, & Seah, 2012). The Big Mac index is therefore an indication if the

currency is under- or overvalued (Clements, Lan, & Seah, 2012). The Big Mac works

very well for representing a bundle of goods described by the PPP, since the

hamburger consists of different raw materials e.g. salad, beef, and cheese and is

therefore a basket on its own (Dewhurst, 2003). McDonald’s is a big brand and

23

restaurants with a standardized menu are located in 119 countries for comparison

(McDonalds Corp., 2013).

The price of a burger is not only dependent on the input to create a hamburger, but

also on wages and the cost of hiring a venue (The Economist, 2009). This view is

strengthen by Parsley and Wei (2007) whom claim that there are very little difference

between the ingredients that makes a hamburger, and therefore the BMI works very

well as a determinant of the correct price for tradable and non-tradable goods. From

these close to perfect conditions the Big Mac is a helpful tool to create the absolute

PPP. To investigate whether the PPP theory holds, and if prices can be standardized,

BMI is a good measure of the current situation worldwide and therefore included in

the test.

5.2.3.2 GDP-DeflatorThe GDP-deflator measures inflation in a country by comparing the current local

currency to the constant local currency1. The deflator is obtained by looking at the

price level from a yearly basket of all new in-country produced goods and services,

and comparing to a base level to assess the index2. The nominal GDP evaluates the

economic worth of transactions in prices for the given period, and thus measures both

volume and price. The constant GDP measures the exact change of volume for goods

and services for the specific time (Chowdhury, 2008).

GDP−Deflator=Nominal GDPRealGDP

×100

It is of importance to measure inflation in comparison to other countries as the

strength of the currency decides the purchasing power. The advantage of the GDP-

deflator is that it covers a broad spectrum of the economy and incorporates the

changes that are subject to both consumption and the monetary policy (Chowdhury,

2008). In comparison to BMI the GDP-deflator is a more widely accepted economic

variable to measure inflation, and thus included to test wheter the PPP-theory holds in

addition to BMI.

1 (http://data.worldbank.org/indicator/NY.GDP.DEFL.KD.ZG).2 (https://www.boundless.com/economics/measuring-nation-s-output-and-income/gdp-trends-using-real-and-nominal-values/calculating-gdp-deflator/).

24

5.2.3.3 Poverty lower limit 2$ The minimum income of $2 a day to survive, have been drawn as a guideline

worldwide (World Bank). There are many negative effects to low income. The poor

may not be able to seek medical care or buy enough food, and the result is decreased

productivity in the country as the society cannot make use of the citizens’ maximal

capacity. Those who are poor tend to have less education or be illiterate that results in

worse jobs that thus have lower wages (UN, 2013).

The poverty line is a generalization of the minimum required income in order to stay

alive, but very useful in determining the situation in a country and how poverty affects

PPP regarding pricing. In countries with a high proportion of poor, the price level after

being adjusted for exchange rates should give the same purchasing power if the

poverty variable has no effect on pricing, but it can be assumed that the prices are

lower and not in accordance with the PPP theory. The poverty variable is used in this

thesis to test if it is possible to find any significant impact between how poor a country

is, the Cost of Living and service pricing.

5.2.3.4 AgricultureIn general, as a society develops, the amount of people working in agriculture

decreases. A majority (75%) of the poorest in the world live in rural areas, and it is

often far to the nearest town. Even in developed countries 45% of the poor live in rural

areas. The only way to make a living is by growing crops or raising livestock, and

therefore agriculture make up 70% of their income (World Bank, 2013). For the

absolute poor, it is of particular importance since agriculture is the best way to improve

their situation due to the fact that they often lack education. It is also positive for the

poorer countries, where food needs are secured, and surplus harvest can be sold and

exported, leading to growth for the entire country (World Bank, 2013). Generally,

where there are more poor people, there are more agriculture and this should affect

prices to be lower, even after adjusting for exchange rates and proof against the

standardization of prices. Lower prices should also have, at lest some impact on the

Cost of Living and it is therefore of great interest to test this variable in the regression

models.

5.2.3.5 GDP/CapitaGDP stands for gross domestic product and is the sum of all economic activity in a

country for 1 year. It measures the consumption of all produced services and goods,

25

investments and adjusted for export minus import. A common welfare measure is

GDP/capita that describes the amount of GDP per person living in the country. The

higher this ratio is the better of is the country economically. There have been a lot of

critiques against the validity of the GDP/capita. Kennedy (1968) argues that it is purely

an economical average and does not actually measures the wellbeing of people e.g.

education, healthcare. GDP/Capita measures how developed/effective a specific

country is, when it comes to output per person. It is therefore interesting to examine

how big impact the factor has together with the Agriculture index and the Poverty

index on Cost of Living and service pricing, to see if there are any linkages between

the effectiveness of a country and the service pricing and Cost of Living.

5.2.3.6 WageIn developed countries, the wage level is generally higher since people in those

countries are more educated and that pushes up wages. The effects are that a higher

wage level creates a beneficial situation for abroad travels and import. In developing

countries the price level is usually lower, which makes the lower wages purchasing

power, in-country, more equal to the developed countries. The factor is included in the

analysis because wage is a main component in service pricing. In order to test if this is

true, the variable is used. Wage in comparison to the price level in the country is a

significant factor after adjusting for exchange rate, for PPP to hold. If the wage to price

level ratio differs more than the exchange ratio, it is proof against PPP.

5.2.3.7 UnemploymentThe higher the unemployment, the more costs to the society due to social security. If

less people are employed, the side effect is that consumption will decline causing

hardship for the entire economy. If employment opportunities are scarce, less people

will invest in education and businesses (Investopedia, 2013). A high unemployment

percentage increases the supply of workers that competes for available jobs, and has a

negative effect on wage. Lower wages cause the cost of service to decrease and is

therefore important to test.

5.2.3.8 Exchange rateA strong currency makes import cheaper, but on the contrary makes export harder

since the goods will be perceived as more expensive by other countries. The exchange

rate ratio, for that reason, has a strong impact on the trading situation. The exchange

26

rate should be a significant factor according to the PPP theory, and is therefore

important in the tests.

5.2.3.9 Service employedToo estimate the value of the service sector; it is useful to know how many percent of

the total workforce is employed in the service industry. This shows the importance of

this sector to the country. The factor is included to examine if the service-employed

level has a significant effect on both the Cost of Living and the service pricing.

5.3 The Regression Model

In the previous part of the paper, the PPP theory was presented and the macro variables

of interest were introduced. To be able to answer the research questions, statistical tests

are required that analyze the economic theory and the variables. The selected

dependent variables are labor cost and Cost of Engineer/Fitter, and it is going to be

examined whether there are any relationships between the variables and the

independent macro variables. An estimation of the variables betas together with a

hypothesis test will determine the statistical and economic significance. Panel data will

be used in the regressions.

There will be three parts to the test since the aim is to investigate the variables impact

on:

1) A general measure (worldwide)

2) Engineers

3) Fitters

The three models of costs can be compared and discussed, for a comprehensive view

and conclusion.

Cost of Living Index=β0+β1∗GDP Deflator+ β2∗Big Mac Index ( PPP )+β3∗Unemployment (% )+ β4∗Agriculture (% )+ β5∗GDP/CAP+β6∗Exchange rate+β7∗WageWorld+β8∗Service employed (% )+β9∗Poverty $ 2

cosT ENG=β0+β1∗GDP Deflator+β2∗Big Mac Index ( PPP )+β3∗Unemployment (% )+β4∗Agriculture (% )+β5∗GD P /CAP+β6∗Exchange rate+β7∗Wag eper country+β8∗Service employed (%)+β9∗Poverty $2

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cosT FIT=β0+β1∗GDP Deflator+β2∗Big Mac Index ( PPP )+β3∗U nemployment ( %)+β4∗Agriculture (% )+β5∗GDP /CAP+β6∗Exchange rate+ β7∗Wag e percountry+ β8∗Service employed (%)+β9∗Poverty $ 2

5.4 Hypothesis

Hypothesis 1: Cost of LivingH 0 : β1+β2+...+β9=0H 1: β1+β2+...+ β9≠ 0

H 0 : The macro factors have no effect on COLH 1:At least one of the macro factors has an effect on COL

Hypothesis 2: Cost of EngineerH 0 : β1+β2+...+β9=0H 1: β1+β2+...+ β9≠ 0

H 0 :The macro factors have no effect on COST_ENGH 1:At least one of the macro factors has an effect on COST_ENG

Hypothesis 3: Cost of FitterH 0 : β1+β2+...+β9=0H 1: β1+β2+...+ β9≠ 0

H 0 : The macro factors have no effect on COST_FITH 1: At least one of the macro factors has an effect on COST_FIT

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6. EMPIRICAL RESULTS6.1 Correlation Results

Table 1 - Correlation between the macro factors in the World regression models; calculations below are based on data observations in 188 countries. The values are adjusted for Robustness. The table shows strong correlation between AW_WAGE and GDP/CAP (0,9332) and the two should therefore not be tested in the same regression model.

AGRI_ UNEMP_ BMI_PPP GDP/CAP GDP_DEF COL_IN EX_RATE SERV_% POVU_2_ AW_WAGE

AGRI_% 1.0000UNEMP_% -0.1121 1.0000BMI_PPP 0.2596 0.0686 1.0000GDPCAP -0.5175 -0.2308 -0.1957 1.0000GDP_DEF -0.0966 0.0055 -0.0786 0.1126 1.0000COL_IN -0.1909 -0.0196 -0.1929 0.5239 0.0906 1.0000EX_RATE -0.3474 0.2064 -0.2102 0.2775 0.0232 0.2691 1.0000Serv_% -0.5472 0.0604 -0.2977 0.3957 0.0110 0.1819 0.3457 1.0000POVU_2_ 0.7741 -0.2132 0.2967 -0.7154 -0.0521 0.0485 -0.3452 -0.5578 1.0000AW_WAGE -0.5428 -0.1257 -0.1368 0.9332 -0.1300 0.7735 0.2102 0.3777 -0.4478 1.0000

AGRI_% = Percentage of the population working in the agriculture sectorUNEMP_% = Percentage of the population unemployed BMI_PPP = Big Mac index – Purchasing Power Parity adjusted GDP/CAP = The GDP/ Capita in Dollar GDP_DEF = The GDP Deflator COL_IN = Cost of Living index, with USA as base countryEX_RATE = Exchange rate, with SEK as base currencyPOVU_2_% = Percentage of the population earning less than 2 dollars/daySERV_% = Service sectors percentage part of the GDPAV_WAGE = Average wage/hour

Table 2 - Correlation between the macro factors in the Flexlink regression models; calculations below are based on the 19 target countries. The values are adjusted for Robustness. The table shows high correlation between the independent variables POVU_2_ and AGRI_, and the two should therefore not be tested in the same regression models.

AGRI_ UNEMP_ BMI_PPP GDPCAP GDP_DEF AV_WAGE EX_RATE ENG_COST FIT_COST POVU_2_ SERV_AGRI_% 1.0000UNEMP_ -0.2606 1.0000BMI_PPP 0.3961 0.3729 1.0000GDP/CAP -0.5854 0.1708 -0.2356 1.0000GDP_DEF 0.0553 0.0142 -0.0475 -0.1924 1.0000AV_WAGE -0.7406 0.1139 -0.2981 0.5044 -0.3334 1.0000EX_RATE -0.0421 -0.2340 -0.2862 0.0680 0.1984 0.0881 1.0000ENG_COST -0.6382 0.0420 -0.2918 0.4465 -0.3226 0.9333 0.1232 1.0000FIT_COST -0.8740 0.1163 -0.3797 0.4941 -0.1295 0.9298 0.1159 0.9492 1.0000POVU_2_ 0.9168 -0.1516 0.5278 -0.5646 0.0487 -0.5572 -0.0291 -0.5186 -0.7258 1.0000SERV_% -0.8478 0.1152 -0.5336 0.4259 -0.0611 0.7893 0.2570 0.7261 0.8952 -0.7094 1.0000

AGRI_% = Value added as a percentage of GDPUNEMP_% = Percentage of the population unemployed BMI_PPP = Big Mac index – Purchasing Power Parity adjusted GDP/CAP = The GDP/ Capita in Dollar GDP_DEF = The GDP Deflator AV_WAGE = Average wage EX_RATE = Exchange rate, with SEK as base currencyENG_COST = Average Engineer cost/hour at Flexlink FIT_COST = Average Fitter cost/hour at Flexlink POVU_2_% = Percentage of the population earning less than 2 dollars/daySERV_% = Service sectors percentage part of the GDP

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6.2 Regression Results

Table 3. Regressions with Cost Of Living as dependent variableThe sample consists of 188 countries 2001-2011. The number of years is 1880. Accounting data, economic data and exchange rate data are collected from Thomson’s DataStream service. The Big Mac Index is collected from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. The dependent variable is Cost of Living (COL_Index), collected from the U.S. Department of State, Bureau of Administration. We average all variables and run the regression on all 188 observations when enough data matching the observations are available. AGRI_% is equal to the value added as a percentage of GDP (in a specific country). UNEMP_% is equal to the percentage of the population (in a specific country) unemployed. EX_RATE is equal to the exchange rate with Swedish Krona as base currency. BMI_PPP is equal to the PPP adjusted Big Mac index with USA as base country. GDP/CAP is equal to GDP per capita measured in Swedish Krona. AW_WAGE is the average total wage in the country. GDP_DEF is almost the same as BMI but with adjusted goods baskets depending on the countries preferences and supply. SERV_% is equal to the percentage working in the service sector. POVU_$2_% is equal to the percentage earning less than 2 dollars a day. The confidence interval is set to 95 %. The degrees of freedom are 1870. The bold numbers are the coefficients, and the values in parentheses are the p-values. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters.

COST OF LIVING INDEX M1 M2 M3 M4 M5 M6 M7AGRI_ % -2.516769 .2560752 -2.548741 -4.080629

(0.000) (0.326) (0.000) (0.000)UNEMP_ % -.3172955

(0.633)BMI_PPP -.0002274 .0157492 -.0000752 .0000175

(0.916) (0.410) (0.965) (0.995)GDP/CAP .0026859 .0005467

(0.000) (0.004)GDP_DEF .4344633 .4122582 .3653433

(0.141) (0.319) (0.188)AV_WAGE .6879482 1.063822 1.015382

(0.000) (0.000) (0.000)EX_RATE .3390573

(0.337)SERV_% .2551647

(0.659)POVU_$2_% -.2782521 .199643

(0.122) (0.061)R2 0.6934 0.1619 0.1921 0.6133 0.5921 0.6446 0.5465N 370 380 930 350 360 470 490

Summary: Strong correlation between the variables AW_WAGE and GDP/CAP (0,9332), and the two are therefore not tested in the same regression model. The models show that AGRI_%, GDP/CAP and AV_WAGE have significant effects on Cost of Living.

Table 4. Regressions with Engineer Cost in Flexlink as dependent variableThe sample consists of 19 Flexlink Sales Units 2001-2011. The number of years is 190. Accounting data, economic data and exchange rate data are collected from Thomson’s DataStream service. The Big Mac Index is collected from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. Wage information from Flexlink is collected manually from each Sales Unit’s Finance Manager. The dependent variable is Cost of an Engineer hour at Flexlink (COST_ENG). We average all variables and run the regression on all or 19 observations. AGRI_% is equal to the value added as a percentage of GDP (in a specific country). UNEMP_% is equal to the percentage of the population (in a specific country) unemployed. EX_RATE is equal to the exchange rate with Swedish Krona as base currency. BMI_PPP is equal to the PPP adjusted Big Mac index with USA as base country. GDP/CAP is equal to GDP per capita measured in Swedish Krona. AW_WAGE is the average total wage in the country. GDP_DEF is almost the same as BMI but with adjusted goods baskets depending on the countries preferences and supply. SERV_% is equal to the percentage working in the service sector. POVU_$2_% is equal to the percentage earning less than 2 dollars a day. The confidence interval is set to 95 %. The degrees of freedom are 180. The bold numbers are the coefficients, and the values in parentheses are the p-values. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters.

COST_ENG M1 M2 M3 M4 M5AGRI_ % -21.63403

(0.003)UNEMP_ % -2.383902

(0.894)BMI_PPP -.0004061

(0.991)GDP/CAP -.0000599 .0000772 .0003627

(0.804) (0.842) (0.352)GDP_DEF -.0425837 -.868106

(0.811) (0.01)AV_WAGE 2.211463

(0.000)EX_RATE -2.609293

(0.620)SERV_% 14.5916 13.74858

(0.000) (0.000)POVU_$2_% .1550995 -5.550969 1.042789

(0.905) (0.091) (0.554)R2 0.8720 0.5316 0.4912 0.2703 0.5542N 190 190 190 190 190Summary: Strong correlation between the variables POVU_$2_% and AGRI_% (0.9168), and the two are therefore not tested in the same regression model. The models show that AGRI_%, SERV_% and AV_WAGE have significant effects on Cost of Engineer.

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Table 5. Regressions with Fitter Cost in Flexlink as dependent variableThe sample consists of 19 Flexlink Sales Units 2001-2011. The number of years is 190. Accounting data, economic data and exchange rate data are collected from Thomson’s DataStream service. The Big Mac Index is collected from The Economist. Agriculture data, unemployment data and poverty $ 2 are collected from World Bank. Wage information from Flexlink is collected manually from each Sales Unit’s Finance Manager. The dependent variable is Cost of a Fitter hour at Flexlink (COST_FIT). We average all variables and run the regression on all or 19 observations. AGRI_% is equal to the value added as a percentage of GDP (in a specific country). UNEMP_% is equal to the percentage of the population (in a specific country) unemployed. EX_RATE is equal to the exchange rate with Swedish Krona as base currency. BMI_PPP is equal to the PPP adjusted Big Mac index with USA as base country. GDP/CAP is equal to GDP per capita measured in Swedish Krona. AW_WAGE is the average total wage in the country. GDP_DEF is almost the same as BMI but with adjusted goods baskets depending on the countries preferences and supply. SERV_% is equal to the percentage working in the service sector. POVU_$2_% is equal to the percentage earning less than 2 dollars a day. The confidence interval is set to 95 %. The degrees of freedom are 180. The bold numbers are the coefficients, and the values in parentheses are the p-values. In the regressions, Huber (1967) –White (1980), standard errors are used to adjust for clusters.

COST_FIT M1 M2 M3 M4 M5 M6 M7AGRI_ % -19.30471 -31.40349

(0.004) (0.026)UNEMP_ % 9.576969 -.628382

(0.534) (0.947)BMI_PPP -.0056208 -.0431647 .0198002 -.0081183

(0.565) (0.664) (0.316) (0.582)GDP/CAP .0001541 .0005871 -.0175516 .0003022 .0000788

(0.629) (0,104) (0.575) (0.238) (0.707)GDP_DEF

1.624974 1.4876AV_WAGE (0.000) (0.000)

EX_RATE .9061424 4.388631(0.778) (0.088)

SERV_% 10.74919 13.4006(0.000) (0.000)

POVU_$2_% 3.603382 -1.594228(0.408) (0.062)

R2 0.5769 0.3365 0.5928 0.6779 0.6541 0.8593N 190 190 190 190 190 190 190

Summary: Strong correlation between the variables POVU_$2_% and AGRI_% (0.9168), and the two are therefore not tested in the same regression model. The models show that AGRI_%, SERV_% and AV_WAGE have significant effects on Cost of Fitter.

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6.3 Analysis of Regressions

6.3.1 Cost of Living Models Basically, to be able to make an accurate statistic analysis, all the variables were tested

for correlation; See table 01. The result of the correlation showed that all variables

except (AW_WAGE; GDP/CAP) were insignificantly correlated. As a result of the

correlation test, the correlating variables will not be tested against each other in the

same regression model. Between (AW_WAGE; GDP/CAP) was a strong positive

correlation of +0,9332, which was not an unexpected result, since a high average wage

will directly affect and increase the GDP/CAP in the country.

The regressions with the large data were tested for heteroscedasticity (White 1980),

and a robust estimation was preformed and the results were accordingly adjusted.

There was a maximum of 188 observations. The regressions showed that GDP/CAP

and AV_WAGE have significant positive effects on the Cost Of Living Index. That

means that a land with a higher GDP/CAP (higher AV_WAGE) has higher Cost Of

Living, compared to a country with lower GDP/CAP (lower AV_WAGE).

By testing the regression for a big dataset, it was possible to prove that agriculture has

a significant negative effect on the Cost Of Living Index. Three out of four tests

showed that AGRI_% has a significant negative impact on COL. Those 3 tests show

low p-values (0,000; 0,001; 0,006) and relatively high R2(0,6934; 0,6446;0,5465). The

three first tests could be seen as much more reliable sources than the fourth test that has

a R2of 0.1921. The result could be misleading in M3 because of the high correlation

between POV_% and AGRI_% (0.7741). The negative effect of AGRI_% implies that,

the higher percentage of GDP that comes from agriculture, the lower the cost of living.

The remaining variables cannot be statistically proven to have an effect on the

COL_Index. UNEMP_ % may not be significant due to subsidy policies and social

safety nets in specific countries, which affects the impact of unemployment. BMI_PPP

and GDP_DEF are measures of inflation, which should be controlled by the

government, to remain at reasonable levels and not negatively affect the economy. The

other factors cannot be fully explained in this examination.

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The result of the regression analysis proved that AV_WAGE, GDP/CAP and AGRI_%

have a significant impact on the Cost of Living Index; therefore the null hypothesis

(hypothesis 1) can be rejected.

6.2.2 Cost of Engineer ModelsAt first, to make a proper statistical analysis, the variables were tested for correlation.

All variables except (AGRI_%; POVU_2_%) were insignificantly correlated. The

correlating variables will not be included in the same model. Between the (AGRI_%;

POVU_2_%) was a positive correlation of +0.9168. This is strengthened by World

Bank’s (2013) findings, that the poorest people in the world live in rural areas, where

the primary income is agriculture.

The regressions were tested for heteroscedasticity (White, 1980), a robust estimation

was performed and the results were accordingly adjusted. There are only 19

observations and 30 are required to be absolutely statistically safe, therefore there

might be errors that affect the conclusions. AW_WAGE is significant in the models

tested and has a positive effect on ENG_COST, explained by wage being a factor in

the total cost. Another significant variable in the models tested is AGRI_% that has a

positive effect in M3 but a negative effect in M6 on ENG_COST. A possible

explanation is that AGRI_% effect on COST_ENG is dependable on the specific

country and therefore provides ambiguous results. The variable SERV_% has an

positive effect on ENG_COST and is significant in 2 out of 2 models , M2 and M5.

SERV_% has probably an effect on COST_ENG but it is not completely statistically

proven.

The reaming six variables cannot be statistically proven to have an effect on

ENG_COST. UNEMP_ % may not be significant due to subsidy policies and social

safety nets in the specific which affects the impact of unemployment. Both BMI_PPP

and GDP_DEF are measures of inflation which should be controlled by the

government, to remain at reasonable levels and not negatively affect the economy. That

GDP/CAP is not significant as in the World regression might be because of our smaller

sample in ENG_COST regression, since it should have a similar effect as wage.

Likewise, POVU_$2_% should have an effect if AGRI_% is significant. The market

adjusts for arbitrage and EX_RATE should not be a problem and have an effect on

ENG_COST.

35

The result of the regression analysis proved that AV_WAGE, SERV_% and AGRI_%

have significant impact on the Cost of Engineers; therefore can the null hypothesis

(hypothesis 2) be rejected. The dependent variable is strongly described in all models

except M4 according to R2.

6.2.3 Cost of Fitters Models To be statistically accurate the variables were tested for correlation. All variables

except (AGRI_%; POVU_2_%) were insignificantly correlated. The correlating

variables will not be included in the same model. The correlation between (AGRI_%;

POVU_2_%) is strengthen by World Bank’s (2013) findings, that the poorest people in

the world live in rural areas, where the primary income is agriculture.

The regressions were tested for heteroscedasticity (White, 1980), a robust estimation

was performed and the results were accordingly adjusted. There are only 19

observations and 30 are required to be absolutely statistically safe, therefore there

might be errors that affect the conclusions. AW_WAGE is significant in the models

tested and has a positive effect on FIT_COST in M6 and M7, explained by wage being

a factor in the total cost. Another significant variable in the models tested is AGRI_%

that has a negative effect in M1 and M3 on FIT_COST probably due to that less

developed countries have more agriculture and therefore lower costs. The variable

SERV_% has a positive effect on FIT_COST and is significant in the models, M4 and

M5. The reason can be that countries with a high service percentage tend to be more

developed.

The remaining six variables cannot be statistically proven to have an effect on

ENG_COST. UNEMP_ % may not be significant due to subsidy policies and social

safety nets in the specific, which affects the impact of unemployment. Both BMI_PPP

and GDP_DEF are measures of inflation, which should be controlled by the government,

to remain at reasonable levels and not negatively affect the economy. That GDP/CAP is

not significant as in the World regression might be because of our smaller sample in

ENG_COST regression, since it should have a similar effect as wage. Likewise

POVU_$2_% should have an effect if AGRI_% is significant. The market adjusts for

arbitrage and EX_RATE should not be a problem and have an effect on ENG_COST.

The dependent variable is strongly described in all models except M2 according to R2.

36

6.3 Survey Results The graphs below show the results from the Flexlink interviews, of selected questions. The questions have a response scale of 1-5, where 1 is Low and 5 is High. Question 6.6 is a YES or NO question. All questions are attached in Appendix I.

37

38

6.4 Analysis Survey

The first part of the interviews, investigates whether it is possible or not, to distinguish

any specific service characteristics between engineers and fitters.

By observing the Graph 1.3, it is possible to distinguish a trend among the answers.

The 7 respondents have all chosen numbers between 3 and 5(agree with the statement),

that the service of a Fitter is quite advanced, and that the work requires qualified

employees with specific knowledge to fulfil the assignments. The same question was

also given for the characteristics of an Engineer at Flexlink (question 2.3). The answers

showed that Engineers are considered to provide an even more advanced service when

comparing to Fitters. The reasoning can be strengthened and proved by looking at the

complementary comments that has been given from the respondents. The respondents

have written that the work of a Fitter is not very advanced, rather easily performed

without firm specific knowledge as long as there are team leaders. It is possible to

reduce the hours worked with increased knowledge and experience of Flexlink’s

parts/products and modules. Experience together with Flexlink specific knowledge,

results in higher efficiency and more well performed work.

Regarding Engineers, the comments on question 2.3 and 2.4 highlighted another

important matter. The core competences at Flexlink are application and design,

executed by the more educated Engineer. The core competences are thereby captured

by the Engineers, and that would support the assumption that the Engineers’ work are

much more advanced compared to the work of a Fitter. The Engineers at Flexlink

undergo continuous internal training, to develop the competence standard.

Flexlink’s projects are customer specific and no jobs are alike, therefore the service is

not standardized. This means that prices vary with respect to the nature of the projects.

It was confirmed in question 6.6 that the sales units regularly use price discrimination;

as a result of the markets’ high price elasticity (question 5.1 and 5.2), the adaptions are

necessary in order to be competitive.

Question 3.3 indicates that the market is very price sensitive and from the interview

questions there are proof of extremely tough competition in some of the markets. The

competition was mainly dependent on price competition, since it was quite easy for the

39

customers to find comparable solutions from a wide range of companies. It appears

that, depending on the pricing of the services, Flexlink can either lose or win a job. As

a result of the service being a main component in the delivery of a project, it is crucial

to set the correct price in order to stay competitive. This is not always true, according

to Flexlink Malaysia, the wage level is much lower in Asia than in Europe and

therefore for the former, wages are of little importance.

7. DISCUSSION

From the PPP theory follows that the prices should be the same after the exchange rate

has been adjusted for, but there are often price differences unexplained by the theory.

There are specific problems relating to services, according to IIHP characteristics, that

affects pricing. The focus of the analysis is the main issues for PPP to hold; primary

international trade and wage that complicate the standardization of service prices.

International Trade

The first obstacle for services to be freely traded internationally, is that the seller and

the customer must often be at same place at the same time for the service to be

performed, the inseparable characteristic. Unlike a commodity, customer relations are

very important and the basis for the customers’ perception of the service. However,

this is very subjective and there might be crucial cultural differences in the societies

regarding power-distance uncertainty avoidance, long-term orientation,

femininity/masculinity, individualism/collectivism (Hofstede, 2001). The PPP theory

requires standardized services in order to compare prices e.g. Big Mac hamburgers,

since the perception of services varies between countries, it is difficult to determine

what is actually sold. In a poor country, a service can be seen as more advanced than in

a more developed country. How easily substituted the service is and the competition,

affects the willingness to pay. In poor countries, a specific service might be regarded as

hi-tech and therefore monopolized or oligopolized due to the lack of competition in the

advanced sector. Less competition reduces the negotiation power of the price, and as

the supply/demand ratio decreases, the prices rise.

One of the main concerns regarding the pricing problem is that the service is

intangible, and what is sold is a contract of a performance. The performances’ results

40

are dependable on both knowledge and cultural background of the customers, and it is

difficult to demonstrate the quality of a service that is not material. The difficulties of

selling a service increase the further away the location of the customer, due to

reputation of the seller and differences in contexts. How the service is perceived can be

linked to heterogeneity, as the service is perceived differently and reviewed from

subjective results, the standardization of pricing becomes problematic. Naturally,

different service outcomes are to be expected as the work is done by people, whom

may have different daily statuses or skills. The level of satisfaction is all about what the

customers expect. How much the customer has "participated" in the process, and the

requirements and specifications incorporated in the service affects the price, the level

of customization. Customized services cannot be standardized and have the same

pricing. The law of one price is therefore difficult to inflict on services since

standardization is rarely possible.

Trade in services is also difficult regarding storage, since the service disappear with the

performance. This is very obvious regarding installation services; when the installation

is complete, the service is over and the only thing that might be left is newfound

knowledge for the observers of the performance. The attainment of knowledge is more

challenging if the level of education in a country/company is low. There might be few

with enough skills to learn the advanced information and perform the service on their

own, making the service seller non-replaceable. Since customers often want

customized services, prefabrication is impossible, making it harder to adapt to business

cycles. A great difference compared to goods adaption to conjuncture, services cannot

take advantage of booms by overproducing due to the non-storage aspect.

For services traded to be internationally available, the people behind the services are

required to be easily moved. This is not always the case, to be able to cross country-

borders, a visa or a proper work permit is necessary. All countries do not allow

unlimited labor immigration, since services are based on human capital; international

trade is restricted and thus violating PPP. There might be language barriers in some

countries where no common language is spoken, causing communication problems and

the perception of the service. How easily workers are willing to move abroad are also

dependent on the working climate; minimum wages and unions. Culture barriers have

also an effect,t since different customs and views might cause disputes and

41

unpleasantness; such issues are religions, women in the workforce or racial

discrimination. Even within the same company’s affiliates, these problems might arise

due to business culture, how things are done and hierarchy issues. There are also added

transaction costs such as relocation, housing and shipping. The obstacles to overcome

in order to trade internationally are proof against the PPP and LOP since the basis of

the theories is free trade for adjusted price and ceased arbitrage situations.

Wage

There are a range of services, all with different specifications and prerequisites.

Consequently, all employed in the service sector, cannot be bunched together and have

the same wage. The necessary background can vary, from apprentice based to a

University master. More advanced services require higher education and therefore an

appropriate wage. How advanced a service is perceived by the costumers, contributes

to the salary’s size. This is a value-based view of how much the service is worth to the

customer, and can even be based on a personal relationship between the worker and the

customer. Wage is also dependent on how advanced the service is and if the worker is

easily replaced due to sector or company specific knowledge. Accounting based costs

that might affect wage are rent and electricity. The supply/ demand ratio can also affect

wage as well as the unemployment ratio. For the PPP theory to hold, the wages should

be appropriate to the cost of living and exchange rates should compensate for the

differences in purchasing power. In the real world, this is unlikely, since there are too

many factors affecting wage that are hard to control for. Wage is therefore not a perfect

fit for the PPP theory’s assumptions.

8. Conclusions

To begin, there are extensive studies on goods pricing, but the research often fails to

cover services. In a world where services account for an increasing percentage of the

economies, we have seen the need to further research the drivers of service pricing.

The focus is whether prices can be standardized or if an adaption to local markets is

necessary. In the background to this issue, the PPP theory states that countries should

have equal purchasing power after adjusting for exchange rates. Nonetheless, even if

this works in theory, the factors not incorporated in the exchange rate refutes the

standardization of prices according to PPP.

42

The literature confirms that the PPP theory does not hold for service pricing, a

consequence of the services’ unique features. A generally accepted service definition is

the IIHP characteristics. The characteristics Intangibility, Inseperability, Heterogenity,

Perishability; complicate and preclude the standardization of services for trade. In fact,

the traded services must be standardized for an international price comparison to be

possible. From our findings the grade of service performance is very subjective and

often dependent on background as well as culture, both company- and country based.

Furthermore, the wages in different countries varies and can hardly give the same

purchasing power for services. If standardization is solely based on adjusting for

exchange rate, purchasing power parity will differ among countries. This further

strengthens that implementing standardized prices are difficult and probably a non-

competitive strategy.

The empirical findings are in line with the literature regarding the problematic

standardization of service pricing. In order to empirically estimate the results, we

created models for our three hypotheses, testing for the validity of the macro variables.

The results are unanimous; more than one macro factor has an effect in Hypothesis 1-3

and the null hypothesis can be rejected in all cases. Wage and AGRI_% are significant

in all models for the dependent variables (Cost of Living; Cost of Engineers; Cost of

Fitters), and SERV_% is significant in the models for two of the dependent variables

(Cost of Engineers; Cost of Fitters) an GDP/CAP is significant in the models for one of

the dependent variables (Cost of Living). The results are consistent and the influencing

variables are accurate as applied to theory. Naturally, both GDP/CAP and AV_WAGE

determines the purchasing power domestically and abroad, AGRI_% is less obvious

but is consistent with higher percentage of agriculture in poorer countries. SERV_% is

significant in the cost of service models as a determinant of the importance of services

internationally. From our models, there is no statistical proof that EX_RATE as the

sole price adjustor in PPP, has an effect on pricing. We conclude that there are too

many factors, not covered by the PPP Theory that acts against an implementation of

standardized pricing.

To further determine the accuracy of the findings, interviews were carried out on

Flexlink with the Finance Managers of seven sales units. The reality based findings

were notably consistent with the theory and statistical results. The two services studied

are engineers and fitters, of which the former are more advanced and require higher

43

education. Flexlink’s projects are customer specific and no jobs are alike, therefore the

service is not standardized. This means that prices vary with respect to the nature of the

projects. It was confirmed that the sales units regularly use price discrimination; as a

result of the markets’ high price elasticity, the adaptions are necessary in order to be

competitive. The case study does not support an international price standardization,

due to the variety of services offered by Flexlink.

Finally, the paper highlights important issues regarding service pricing and contributes

to an increased awareness. The analysis methodology is based on our interpretations of

relevant economic aspects. First, the service needs to be standardized in order to

compare prices. For the PPP Theory to hold, prices must be adjusted for more factors

than the exchange rate in order to achieve the same purchasing power internationally.

Furthermore, pricing standardization is difficult since the factors impacts on local

markets are difficult to determine. A local price adaption is the most strategic approach

to cope with the differences. We conclude that a standardization of service pricing is

not feasible based on the findings.

9. Limitations and Suggestions

As has been described in the paper, the present study contains some interesting

findings about the factors affecting service pricing and Cost of Living. However, there

are some limitations that limit the power of this thesis analysis. Firstly, the data used

for the Flexlink regression includes only 19 sales units within one company in the

conveyor industry. Because of the few observations, and that only one company and

one sector is studied, we cannot extend the results of this study to other industries.

Furthermore, in order to study differences across countries and across industries and

their effects on service pricing, more companies in more countries should be included

in the study. Bigger datasets would give a more accurate result to which macro factors

that affect service pricing on a global level.

One other restriction of the study is that we have only used one theory (PPP). There

are probably other theories that could be applicable to explain the service pricing that

we did not use in this paper. We have not been able to find any similar studies in the

field of factors affecting service pricing (other than accountings studies), and the

44

subject is relatively unexplored, which has had a serious impact on the conclusions

since we lack a reference paper. Most of the literature regarding pricing, concern

pricing of products, which could have affected the outcome of our study. The paper is

written by bachelor students, as a consequence there might be lack of knowledge and

execution in comparison to an e.g a postgraduate.

We suggest that further research is made on bigger datasets that includes more

companies in different industries, in more than thirty countries. By comparing

different industries and different areas around the world, the researcher would maybe

find other possible trends regarding service pricing. It would also be interesting to

measure the level of competition within an industry and see how that affects service

pricing.

45

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50

Interviews and Observations

Flexlink Internal Information Power Point (2013), 1(1)

Melanie Saugere, Finance Manager, Flexlink France

Neus Anglès, Financial Controller, FlexLink Spain

Radosław Masztalerz, Financial Controller, FlexLink Poland

Susanne Lager, Finance Manager, Flexlink Sverige

Monika Kocsner, Finance Manager, Flexlink Hungary

Robyn Kubeil, Finance Manager Flexlink Australia

Cherry Lee, Finance Manager Flexlink Malaysia

51

Appendix

Table 6- Significance between the factors in World regression, adjusted for Robust

AGRI_ UNEMP_ BMI_PPP GDPCAP GDP_DEF COL_IN EX_RATE SERV_ POVU_2_ AW_WAGE

AGRI_ 1.0000

UNEMP_ -0.1121 1.00000.1780

BMI_PPP 0.2596 0.0686 1.00000.0631 0.6255

GDP/CAP -0.5175 -0.2308 -0.1957 1.00000.0000 0.0069 0.1686

GDP_DEF -0.0966 0.0055 -0.0786 0.1126 1.00000.2157 0.9459 0.5797 0.1702

COL_IN -0.1909 -0.0196 -0.1929 0.5239 0.0906 1.00000.0189 0.8237 0.1708 0.0000 0.2683

EX_RATE -0.3474 0.2064 -0.2102 0.2775 0.0232 0.2691 1.00000.0281 0.1841 0.2185 0.0830 0.8827 0.0931

SERV_% -0.5472 0.0604 -0.2977 0.3957 0.0110 0.1819 0.3457 1.00000.0000 0.4693 0.0321 0.0000 0.8878 0.0254 0.0289

POVU_2_ 0.7741 -0.2132 0.2967 -0.7154 -0.0521 0.0485 -0.3452 -0.5578 1.00000.0000 0.0413 0.1252 0.0000 0.6030 0.6281 0.1606 0.0000

AW_WAGE -0.5428 -0.1257 -0.1368 0.9332 -0.1300 0.7735 0.2102 0.3777 -0.4478 1.00000.0019 0.4929 0.4793 0.0000 0.4856 0.0000 0.2831 0.0396 0.1944

Table 7 - Significance between the factors in Flexlink’s regression, adjusted for Robust

AGRI_ UNEMP_ BMI_PPP GDPCAP GDP_DEF AV_WAGE EX_RATE ENG_COST FIT_COST POVU_2_ SERV_AGRI_ 1.0000UNEMP_ -0.2606 1.0000

0.2812BMI_PPP 0.3961 0.3729 1.0000

0.0932 0.1159

GDPCAP -0.5854 0.1708 -0.2356 1.00000.0085 0.4846 0.3316

GDP_DEF 0.0553 0.0142 -0.0475 -0.1924 1.00000.8221 0.9541 0.8467 0.4301

AV_WAGE -0.7406 0.1139 -0.2981 0.5044 -0.3334 1.00000.0003 0.6425 0.2151 0.0277 0.1631

EX_RATE -0.0421 -0.2340 -0.2862 0.0680 0.1984 0.0881 1.00000.8642 0.3350 0.2349 0.7821 0.4156 0.7199

ENG_COST -0.6382 0.0420 -0.2918 0.4465 -0.3226 0.9333 0.1232 1.00000.0033 0.8644 0.2254 0.0553 0.1780 0.0000 0.6152

FIT_COST -0.8740 0.1163 -0.3797 0.4941 -0.1295 0.9298 0.1159 0.9492 1.00000.0001 0.7052 0.2006 0.0861 0.6732 0.0000 0.7062 0.0000

POVU_2_ 0.9168 -0.1516 0.5278 -0.5646 0.0487 -0.5572 -0.0291 -0,5186 -0,7258 1.00000.0000 0.5355 0.0202 0.0118 0.8431 0.0132 0.9058 0.0229 0.0050

SERV_ -0.8478 0.1152 -0.5336 0.4259 -0.0611 0.7893 0.2570 0.7261 0.8952 -0.7094 1.00000.0000 0.6387 0.0186 0.0691 0.8039 0.0001 0.2881 0.0004 0.0000 0.0007

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