1

Determinants of capital budgeting methods use

– comparative survey of companies practice in Poland and Thailand

Tomasz Wnuk-Pel (corresponding author)*1

Pattanant Petchchedchoo**2

Kanitsorn Terdpaopong***3

Abstract

The research focuses on the investigation of determinants for the choice of capital

budgeting methods (CBM) in Poland and Thailand. Combining the data on CBM use with a

rich set of dependent variables enabled identification of influence of certain companies

characteristics, chief financial officer’s (CFO) characteristics and magnitude of capital

expenditure budget (CAPEX) on the use of CBM. As the results suggest that there are

significant differences between countries when using CBM, the decision was made to test the

model separately on Polish and Thai samples. In the case of Polish companies the regression

results are not very satisfactory, the best explained dependent variables are NPV (R2 = 0.373)

and IRR (R2 = 0.323). The regression results are much better in the case of Thai sample where

for every CBM the fit is very satisfactory and ranges from R2 = 0.532 in the case of audit

during implementation to R2 = 0.884 in the case of IRR.

Keywords: management accounting, capital budgeting, Poland, Thailand, survey, investment

decisions.

1. Introduction

This study explores the influences on Polish and Thai companies adoption of capital

budgeting methods (CBM). This area of research is important because capital budgeting

decisions are one of the most important areas of company finance management. Poland and

Thailand have been chosen for the research because both countries although rapidly

* dr. hab. Tomasz Wnuk-Pel, tomwnuk@uni.lodz.pl, Matejki 22/26, 90-237 Lodz, Department of Accounting,

Faculty of Management, University of Lodz, POLAND. **

prof. Pattanant Petchchedchoo, Dean of Faculty of Accountancy, pattanant.peo@dpu.ac.th, 110/1-4

Prachachuen Road, Laksi District, Bangkok 10210, Faculty of Accountancy, Dhurakij Pundit University,

THAILAND. ***

prof. Kanitsorn Terdpaopong, Associate Dean for International Affairs, kanitsorn@rsu.ac.th, 52/347

Paholyothin Road, Pathumthani 12000, Faculty of Accountancy, Rangsit University, THAILAND.

2

developing in recent years, still remain less developed in many respects in comparison to

developed economies in which most of the research were conducted so far. Both countries

also represent typical economies for Central and Eastern Europe – CEE and Asia and in both

countries research on capital budgeting practice remains seriously underdeveloped. Although

the process of diffusion of CBM in developed countries (especially in large companies) is

almost complete (e.g. Graham, Harvey, 2001; Ryan,and Ryan, 2002; Hermes et al., 2007;

Truong et al., 2008), this is not the case for Poland and Thailand(e.g. Zarzecki, 1997; Szychta,

2001; Rogowski, Kasiewicz, 2006;Rajatanavin,Venkatesh, 2007; Wnuk-Pel, 2011; Andoret

al., 2011; Wnuk-Pel, 2013; Olufemi,Adegbola, 2013; Champathed,Chansa-ngavej, 2015).The

study will focus on narrowing the gap between theory and practice of capital budgeting in

developing countries in CEE and Asia by measuring the extent to which theoretical concepts

are adopted in practice. The results of the survey will be useful for practitioners as they will

learn more about capital budgeting practices in these countries.

Capital budgeting practice has drawn the attention of researchers all over the world for

many years but vast majority of the studies dedicated to it was conducted in highly-developed

countries, mostly in North America, Australia and Western Europe, e.g. Australia (Truong et

al., 2008), Canada (Graham, Harvey, 2001), France (Brounenet al., 2004), Germany

(Brounenet al., 2004), the Netherlands (Hermes,Smid, 2007), Sweden (Sandahl,Sjögren,

2003; Daunfeldt,Hartwig, 2011), the UK (Brounenet al., 2004), the USA (Graham, Harvey,

2001; Ryan, Ryan, 2002). The results of these studies are widely known, especially in

academic circles, and they undoubtedly had an influence on the development of theory and its

teaching as well as its practical use.Although there were so far surveys focusing on capital

budgeting methods diffusion in Poland and Thailand (e.g. Zarzecki, 1997; Szychta, 2001;

Rogowski, Kasiewicz, 2006, Rajatanavin, Venkatesh, 2007; Wnuk-Pel, 2011;Andoret al.,

2011; Wnuk-Pel, 2013;Olufemi, Adegbola, 2013; Champathed,Chansa-ngavej, 2015; ), yet

their results were partial and usually focused only on the extent of different CBM diffusion

lacking more detailed analysis.

As far as companies practice in use of CBM is concerned in Poland,Szychta (2001) found

that 30% of companies use net present value (NPV) and 25% internal rate of return (IRR).

The research conducted ten years later (Wnuk-Pel, 2011) showed that diffusion of these

methods increased to 53% (NPV) and 47% (IRR) – these results were confirmed by Andoret

al.(2011), who found that 58% of Polish companies use discounted cash flow (DCF)

techniques. What is also interesting, together with the increase in use of methods based on

DCF, also other methods (e.g. payback – PB or accounting rate of return – ARR) are more

3

popular than before. While Szychta (2001) found that these methods were used by 40% and

35% of the companies respectively, Wnuk-Pel (2011) found that their use increased to 81%

and 59% (Wnuk-Pel’s findings were confirmed by Andoret al.(2011), who found their use on

the level of 61% and 68% respectively). The studies mentioned above focused mainly on

capital budgeting methods diffusion however, and did not contained more detailed analysis of

their use and especially ignored influences on CBM practice.

The situation in Thailand is quite similar. The study by Champathed and Chansa-ngave

(2015) confirmed that the captail budgeting techniques were used by Thai firms especially on

investment projects (74.1%) and the most popular methods were IRR, payback period and

NPV (17.0, 14.1, and 11.9 % respectively). The methods used were the same as in the studies

of Rajatanavin and Venkatesh, (2007) and OlufemiandAdegbola (2013) wherethey made a

comparison of the capital budgeting used by Thai and US firms and found that payback

period was the most popular method among Thai firms followed by net present value and

internal rate of return while in the US, most popular method was internal rate of return

followed by net present value and hurdle rate.Even though such capital budgeting methods

have been concerned, Champathed and Chansa-ngavej (2012) suggested that researchers

should investigate other variables besides what had been used and studied as criterion to

determine capital investment projects. Most financial managers used capital budgeting

techniques but not for all projects. Many Thai firms used both capital budgeting techniques

and non-financial data; many firms used combination of techniques.

Although there were some studies on CBM methods diffusion in Poland and Thailand, yet

the use of these methods is not researched enough, especially when compared to research

carried out in more developed countries. Studies of capital budgeting practices in companies

based in Poland and Thailand seem interesting due to the historical conditioning of these

countries and their recent development. Poland have been undergoing political

transformations which started at the end of the 1980’s and resulted in profound changes in the

country economy, which over the years have come a long way from communism to

capitalism, and since the late 90’s of twenty centuryPoland has been integrating with

European Union structures (from 2004 Poland is a member of European Union). Polish

economy opened to foreign capital and companies operating in Poland have to compete with

foreign companies locally and more often globally. The competition manifests itself inter alia

in investments undertaken by companies operating in Poland and which, for the sake of

efficient competitiveness with other firms, must be effective – it requires both good business

ideas and proper use of the evaluation of these ideas (investments) – methods which are

4

widespread and commonly used in companies based in more developed countries(e.g.

Graham, Harvey, 2001; Ryan, Ryan, 2002; Hermes et al., 2007; Truong et al., 2008).

Thailand hasthe population over 65 million, literacy rate 96%, GDP per Capita 5,778.98

USD ‎(2013) and 387.3 billion USD ‎(2013). The GDP growth rate in Thailand averaged 0.94

percent from 1993 until 2015, reaching an all times high of 11.20 percent in the first quarter

of 2012 and a record low of – 11.10 percent in the fourth quarter of 2011 and expanded to

0.30 percent in the first quarter of 2015 over the previous

quarter.(http://www.tradingeconomics.com/thailand/gdp-growth). Thailand is classified as

a developing country and has traditionally been a major rice exporter. Rice and tourism

industries are important source of foreign currency earnings of the country. From mid-1980

till 1997, Thailand experienced a booming economy and double digit growth, but in June

1997 the country experienced an abrupt slowdown of the economy to less than 2 percent

growth. Most businesses suffered from the economic crisis. After the economic crisis in

1997, the growth average of GDP was just 2.6% annually in 2009-14. Tourism earnings are

likely to improve notably in 2015. Thailand’s Board of Investment (BOI) is intensifying

efforts to take capital investment to the country and has recently set list of 13 targeted

industries covering 61 business activities to promote in special economic zones, while

relaxing rules and regulations on used machinery (BOI Press Release; 16 April 2015).

The research on capital budgeting conducted so far in Poland and Thailand did not address

sufficiently such questions as: (a) are thereany differences in using of CBM between

companies of different characteristics? (b) are there differences in using of the methods

between companies with different CFO’s characteristics?, (c) are the use of CBM influenced

by the magnitude of capital expenditure budget or (d) is the process of investment appraisal

formalised, (e) and is the diffusion of CBM similar in companies in Poland andThailand?

In the context of the above questions, the aim of the research was formulated – its aim was

to study the practice of capital budgeting in companies operating in Poland and Thailand and

in particular to analysediffusion of capital budgeting methods among companies and factors

which influence their selection. Aim of the study is fundamentally concurrent with aims of

similar studies conducted in the world (e.g. Warfield et al., 1995; Pike, 1996; Klassen, 1997;

Arnold, Hatzopoulos, 2000; Graham, Harvey, 2001; Anand, 2002; Sandahl,Sjögren, 2003;

Brounenet al., 2004; Verbeeten, 2006; Hermes,Smid, 2007; Leon et al., 2008; Truong et al.,

2008; Holmen,Pramborg, 2009; Vermaet al., 2009; Bennounaet al., 2010; Andoret al., 2011;

Hartwig, 2012; Ahmed, 2013; Daunfeldt,Hartwig, 2011), however some aspects were slightly

different. Firstly, this study was carried out on a sample of companies operating in Poland and

5

Thailand, countries which are different in terms of culture, institutions or significance of

capital market for the economy from developed countries where most of the surveys were

carried out. Secondly, the study not only aimed to present capital budgeting methods used, but

also focused on the analysis of procedures and organization of capital budgeting process.

Thirdly, this study explores not only the use of capital budgeting methods (like all studies

done so far in these countries) but also factors that determine their selection.In these respects,

the study is unique.

It should be stressed that capital budgeting decisions are much more than the application of

CBM such as NPV, IRR, ARR etc. to evaluate and rank investment opportunities. Capital

budgeting decisions comprise general management problems (Miller, O’Leary, 2007). Formal

procedures analyzed in the paper address only a small proportion of the process of capital

budgeting decision making. The research concentrates on analyzing evidence on the formal

usage of known evaluation techniques and it is an effort to broaden the knowledge and

understanding of investment appraisal practices, the research of which, in Poland and

Thailand, remains seriously underdeveloped.

The rest of the paper is organized as follows: first the hypotheses are developed

andtheoretical model underlying this research is discussed, which is followed by a short

presentation of the research method. Then the results of the research in terms of capital

budgeting methods used and factors determining their use are analyzed. The paper finishes

with conclusions.

2. Hypotheses development and theoretical model

When analysing diffusion of capital budgeting methods in Polish and Thai companies we

expect (according to literature) that certain company characteristics will influence the use of

CBM. In particular we expect companies listed on stock exchange (PUB) will use CBM more

often than companies which are not listed. It can be suggested that listed companies are

generally bigger, better managed, more sophisticated and having appropriate resources to use

these methods (e.g. Brounenet al., 2004).Anand (2002) found that public companies use

sensitivity analysis more often than private companies and Graham and Harvey (2001) found

that public companies are significantly more likely to use NPV and IRR than are private

companies. As far as company main activity is concerned we expect manufacturing

companies (MAN) will use CBM more often than non-manufacturing companies

(manufacturing companies are often larger and they realize bigger capital investment projects

– e.g. Daunfeldt,Hartwig, 2011). As foreign ownership is concerned we expect companies

6

with foreign capital (FOWN) use CBM more often than companies with only domestic

capital, because companies in more developed countries (from which the capital usually

comes from) use these methods more often than companies in Poland or Thailand (e.g.

Graham, Harvey, 2001; Ryan, Ryan, 2002; Hermes et al., 2007; Truong et al., 2008), some

research however did not confirm this results (Leon et al., 2008). Another variable

characterizing companies taken into account in the research was management ownership – we

expect companies owned by managers (MANOWN) will use CBM more often than

companies which are not owned by managers. Management ownership can influence

decisions made (e.g. Warfield et al., 1995; Klassen,1997), managers/owners have more to

lose if company has significant problems and it may make managers to use these methods

more often. Literature suggest that company size is one of the most important variables

influencing CBM selection – we expect larger companies (LSIZE) will use CBM more often

than small companies (e.g. large companies have resources to use more sophisticated methods

and they are also dealing with bigger projects making the use of more sophisticated methods

cheaper – e.g. Pike, 1996; Payne et al., 1999; Graham, Harvey, 2001; Sandahl,Sjögren, 2003;

Brounenet al., 2004; Verbeeten, 2006; Hermes et al., 2007; Bennounaet al., 2010; Andoret

al., 2011; Daunfeldt,Hartwig, 2011; Correia, 2012; Hartwig, 2012; Ahmed, 2013). Also sales

direction could influence capital budgeting method selection – we expect companies with

foreign sales (FSALES) will use CBM more often than companies with no foreign sales.

Companies with significant proportion of sales abroad must compete globally with large and

efficient competitors from abroad often using these methods and what is more high

uncertainty of doing business abroad may increase the use of risk assessment methods

(Daunfeldt,Hartwig, 2011). Hermes et al. (2007) showed that Chinese companies with foreign

sales use NPV more often than companies with no foreign sales,also Holmen and Pramborg

(2009) showed that the use of payback can increase with increase of political risk which is

connected with foreign sales (it should be noted that payback may be used as a rough risk

measure).The literature suggest that company leverage and dividend payment can influence

capital budgeting method selection. As leverage is concerned we expect companies with high

leverage (HLEV) will use CBM more often than companies with low leverage (e.g. Graham,

Harvey, 2001; Daunfeldt,Hartwig, 2011 and Ahmed, 2013 found that leveraged companies

use NPV more often). Graham and Harvey (2001) also showed that leveraged companies

more often use sensitivity and scenario analysis. It may be suggested that highly geared

companies often use bank loans to finance their investments and it is a common practice that

banks require use of these methods before they agree to finance investments. It can also be

7

found in the literature (e.g. Binder,Chaput, 1996; Daunfeldt,Hartwig, 2011; Hartwig, 2012;

Ahmed, 2013) that highly leveraged companies use payback more often than companies with

low leverage (the explanation for this could be that payback use is associated with uncertainty

and geared companies are more risky). If we take into account dividend payment, we expect

companies paying dividends (DIV) will use CBM more often than companies not paying

dividends.Daunfeldt and Harvey (2011) found that companies paying higher dividends use

DCF methods and sensitivity analysis more often than those paying lower dividends. Graham

and Harvey (2001) found that companies paying dividends use NPV, IRR and sensitivity

analysis more likely than companies that do not pay dividends. Hence, we hypothesize:

H1: company characteristics, such as public ownership, manufacturing activity, foreign

ownership, management ownership, large size, foreign sales, high leverage and dividend

payment, influence the frequency of capital budgeting methods selection.

While analysing the influence of certain chief financial officer (CFO) characteristics, we

expect they will influence the frequency of CBM selection. In particular we expect companies

with young CFO (YOUNG) will use CBM more often than companies with old CFO.

Literature (e.g. Hermes et al., 2007; Daunfeldt,Hartwig, 2011) seem to suggest this as

younger managers can be more familiar with more sophisticated methods and they may be

also more open in their use. Hermes et al. (2007) showed that younger CFO use NPV (and

other methods) more often than older CFO. We also expect companies with CFO highly

educated (HEDU) in business/economics will use CBM more often than companies with CFO

not highly educated (Leon et al., 2008; Ahmed, 2013). For managers which are better

educated in business/economics the use of these methods may seem to be “natural”, they may

use these methods more often because they were “taught” to do so (e.g. Hermes et al., 2007;

Ahmed, 2013).Anand (2002) found that better educated CFO use sensitivity analysis more

often than CFO not having higher education in business/economics. According to our

expectations companies with short tenure CFO (STEN) will use CBM more often than

companies with long tenure CFO. CFO which are not a long time in the company may tend to

use these methods more often as they are more widely acceptable. In contrast CFO which are

long time in their position may tend to use their judgment and experience more often and thus

prefer simpler methods viewing them as “not that bad” (Daunfeldt,Hartwig, 2011). Thus, we

hypothesize:

8

H2: chief financial officer characteristics, such as young age, high education and short

tenure, influence the frequency of capital budgeting methods selection.

When analysing diffusion of capital budgeting methods we expect (according to literature)

that size of company’s capital expenditure budget will influence the use of CBM, more

specificallywe expect companies with larger capital budgets (LCAPEX) will use CBM more

often than companies with small capital expenditure budgets (use of more sophisticated

methods in the case of large projects is comparatively less costly than in small projects – e.g.

Hermes et al., 2007).Vermaet al. (2009) showed that companies with large CAPEX use NPV

more often than those with small CAPEX (the difference was not significant for other

methods),similar results were obtained by Correia (2012). Some studies however show no

significant differences in CBM use in relation to size of CAPEX (Leon, 2008). Hence, we

hypothesize:

H3: large size of company’s capital expenditure budget influence the frequency of capital

budgeting methods selection.

When analysing the degree of diffusion of capital budgeting methods it is interesting to

look at and compare the practices of different countries. Poland and Thailand have been

chosen for the research for several reasons: (a) both countries, although rapidly developing in

recent years, still remain less developed in many respects in comparison to more developed

economies in which most of the comparative research were conducted so far, (b) both

countries represent developing economies typical for CEE and Asia, (c) in both countries

research on capital budgeting practice remains seriously underdeveloped.

Between country comparisons were rare in the literature but one can mention research by

Payne et al. (1999), Graham and Harvey (2001) or Bruonenet al. (2004). These notable

exceptions in research concentrate however on the determinants of capital budgeting practices

for a number of developed countries (The Netherlands, Germany, France, Canada, the US and

the UK). There isthe example of comparison in capital budgeting practice of developing

Central and East European (CEE) countries (Andoret al., 2011) and also the research (Hermes

et al., 2007) comparing practices in developed European country (The Netherlands) with

developing Asian economy (China). The comparative research done so far generally suggest

that diffusion of capital budgeting methods is greater in developed than developing countries.

Hermes et al. (2007),found the differences in capital budgeting diffusion among the countries

9

of different level of development (Dutch companies on average use more sophisticated capital

budgeting techniques than Chinese firms). Research by Brounenet al. (2004) found some

country differences, but when controlling for the underlying variation in firm size, exchange

listing, CEO education and shareholder orientation, they lost much of their impact. Taking

into account the research so far and also the fact that Poland and Thailand can both be

regarded as developing countries we hypothesize:

H4:there is no difference between the use of capital budgeting methods by Thai and Polish

firms.

To test the hypotheses formulated above, the set of dependent and independent variables

were set together to formulate the theoretical model (Figure 1).

Figure 1.Theoretical model for the study

3. Research method

Survey research method has been selected to verify adopted hypotheses. Despite many

shortcomings of research carried out by means of survey research (in comparison to case

study method which enables to analyse in greater detail actual practices used in companies),

the authors are convinced that it will facilitate unique analysis of companies’ practice in

Poland and Thailand in terms of capital budgeting and it will contribute to modification of

existing beliefs on the use of methods and factors influencing their use (it enables comparison

influence

influence

influence

CAPITAL

BUDGETING

METHODS:

Formalization

of investment appraisal

Investment appraisal

methods used

Discount rate used

in DCF methods

Methods

of risk assessment

PUB

MAN

FOWN

MANOWN

LSIZE

FSALES

HLEV

DIV

Company

characteristics

CFO

characteristics

CAPEX

size

YOUNG

HEDU

STEN

LCAPEX

10

in time dimension – with previous studies and also in space – between companies in Poland

and Thailand). Another argument which made the authors use survey research was the desire

to compare the study results with results of research conducted in other countries (e.g.

Warfield et al., 1995; Pike, 1996; Klassen, 1997; Arnold, Hatzopoulos, 2000; Graham,

Harvey, 2001; Anand, 2002; Sandahl,Sjögren, 2003; Brounenet al., 2004; Verbeeten, 2006;

Hermes,Smid, 2007; Leon et al., 2008; Truong et al., 2008; Holmen,Pramborg, 2009;

Vermaet al., 2009; Bennounaet al., 2010; Andoret al., 2011; Hartwig, 2012; Ahmed, 2013;

Daunfeldt,Hartwig, 2011). As broad and rich overview of capital budgeting practice has never

(according to authors knowledge) been made in Poland and Thailand before. The study is

therefore unique.

In order to analyse capital budgeting methods diffusion and factors influencing their

selection in companies operating in Poland and Thailand the respondents were asked four

groups of questions (questionnaire is included in Appendix 1):

1. company characteristics (11 questions),

2. chief financial officer’s characteristics (3 questions),

3. organization of investment process (4 questions),

4. use of investment appraisal methods (5 questions).

The questionnaire contained both one-choice and multiple-choice questions, but

respondents were asked to provide more expansive answers and comments (questions 4.1, 4.2,

4.3, 4.4 and 4.5). In several questions (questions 3.4, 4.1, 4.2 and 4.3) 5 grade Likert scale

was used and the answer “never” has “1” value, “rarely” has value “2”, “occasionally” has

value “3”, “often” has value “4” and “always” has value “5”. Only companies which

answered “often” or “always” are classified as users of the method.

The authors pre-tested survey instrument on fellow colleagues at their Faculties first and

after some corrections tested it again on the small group of practitioners in both countries

which was also followed by some changes in the questionnaire. When distributing final

version of the questionnaire, the authors made sure that respondents understand that capital

budgeting decisions refer to all non-routine investments – if it would not be clear, respondents

would probably not be able to provide credible answers.

The questionnaire was delivered to the companies listed on Polish and Thai stock

exchanges (Warsaw Stock Exchange and the Stock Exchange of Thailand) and to hand-picked

selected non-listed (private) companies using convenience sampling method. In general, 819

questionnaires were distributed in Poland (495 among listed and 324 among private

companies) and 800 in Thailand (500 among listed and 300 among private companies). The

11

authors received, 107 properly filled questionnaires in Poland (33 from listed and 74 from

private companies) and 220 in Thailand (52 from listed and 168 from private companies) after

leaving incomplete questionnaires. Thus the response rate was in general 20.2% (13.1% in

Poland and 27.5 % in Thailand). In total 327 samples from Poland and Thailand were used in

the study.

Capital budgeting practice involves numerous methods which managers can choose to

facilitate their decisions. Among these methods one can distinguish investment appraisal

methods such as NPV, IRR etc. and risk assessment methods such as sensitivity or scenario

analysis. The research so far used different classifications of CMB (Arnold,Hatzoppoulos,

2000; Graham, Harvey, 2001; Anand, 2002; Sandahl,Sjogren, 2003; Ryan, Ryan, 2002;

Brounenet al., 2004; Liljeblom,Vaihekoski, 2004; Danielson, Scott, 2006; Verbeeten, 2006;

Hermes et al., 2007; Leon et al., 2008; Truong et al., 2008; Bennounaet al., 2010; Andoret

al., 2011; Ahmed, 2013; Daunfeldt,Hartwig, 2011). In the present research generally no

specific classification of CBM from previous surveys was used, the research instead

concentrated on the examination of the investment appraisal and risk analysis methods which

were used in most of the studies conducted so far (the purpose of concentrating on variables

most commonly used in the previous studies was to obtain reach comparison of the results

with other surveys).

In the present research it was also examined which methods of cost of capital estimation

for DCF techniques are used in Poland and Thailand. Although not all of the studies

mentioned above are examining this issue we wanted to analyze it in a greater detail as this

research area is not developed in Poland and Thailand enough. We also wanted to compare

the results with studies conducted in different countries e.g. Arnold,Hatzoppoulos

(2000),Anand (2002),Ryan, Ryan (2002),Brounenet al. (2004),Liljeblom,Vaihekoski

(2004),Block (2005),Verbeeten (2006), Hermes et al. (2007),Leon et al. (2008), Truong et al.

(2008),Burns, Walker (2009),Bennounaet al. (2010).

Not a lot of research conducted so far (e.g. Burns, Walker, 2009; Bennounaet al., 2010)

examined the issues concerning formalization of investment appraisal process. To analyze

these issues we took as dependent variables: formalization of evaluation before investment

decision, monitoring investment during implementation and post-investment audit. All capital

budgeting methods analyzed are shown in Table 1.

12

Table 1.Capital budgeting methods analysed

Capital budgeting method Symbol

Formalization of investment appraisal:

- formal evaluation before investment decision FORMAL_APR

- monitoring investment during implementation AUD_DUR_IMPLEMENT

- post-investment audit AUD_POST_INVEST

Investment appraisal method used:

- Net Present Value (NPV) APR_NPV

- Internal Rate of Return (IRR) APR_IRR

- Payback (PB) APR_PB

- Discounted Payback (DPB) APR_DPB

- Accounting Rate of Return (ARR) APR_ARR

Discount rate used in DCF methods:

- Weighted Average Cost of Capital (WACC) COST_WACC

Methods of risk assessment:

- sensitivity analysis A_SENSITIVITY

- scenario analysis A_SCENARIO

Capital budgeting methods specified in Table 1 will serve as dependent variables and it

will be surveyed if (how often) they are used and what (independent variables) influence their

use. Hypothesis 4 was tested by statistical comparison of capital budgeting practice in Poland

and Thailand whereas hypotheses 1-3 were tested with a multiple regression inthe form

shown in Equation 1 (this is a modified version of equation used by Daunfeldtand Hartwig,

2014).

CBMij = 0 + 1PUBi + 2MANi + 3FOWNi + 4MANOWNi + 5LSIZEi

+ 6FSALESi + 7HLEVi + 8DIVi + 9YOUNGi + 10HEDUi

+ 11STENi + 12LCAPEXi + i [Equation 1]

where:

- CBMij is reported use of capital budgeting method j (j – 1, 2…11; see Table 1) by the

company i (i = 1, 2…n);

- PUBi is the type of ownership of the company i (i = 1, 2…n) (if the company is listed on

stock exchange it is regarded as public – PUB, if the company is not listed on stock

exchange it is regarded as private – PRIV);

13

- MANi is the type of activity the company i (i = 1, 2…n) is engaged in (if the company is

manufacturing – MAN, if the company is not manufacturing – NMAN);

- FOWNi is foreign ownership of the company i (i = 1, 2…n) as defined by the percentage of

shares owned by foreign capital (if there is foreign ownership (any percent) – FOWN, if

there is not foreign ownership – NFOWN);

- MANOWNi is the share of the company i (i = 1, 2…n) owned by top three managers

ranging from less than 5% to more than 20% (if less than 5% of shares is owned by top

three managers – NMANOWN, if more than 5% of shares is owned by top three managers

– MANOWN);

- LSIZEi is the size of the company i (i = 1, 2…n) as defined by the number of employees

ranging from less than 10 to more than 1000 employees (if company has less than 250

employees it is defined as SMALL, if company has more than 250 employees it is defined

as LARGE)4;

- FSALESi is the proportion of sales abroad of the company i (i = 1, 2…n) ranging from 0%

to more than 50% (if foreign sales are up to 25% the company is defined as not having

foreign sales – NFSALES, if foreign sales are more than 25% the company is defined as

having foreign sales – FSALES);

- HLEVi is total debt to asset ratio of the company i (i = 1, 2…n) ranging from 10% to more

than 50% (if leverage is up to 25% the company is defined as having low leverage –

LLEV, if leverage is more than 25% the company is defined as having high leverage –

HLEV);

- DIVi is the dividend policy of the company i (i = 1, 2…n) (if the company pays dividends –

DIV, if the company does not pay dividends – NDIV);

4European Union defines small and medium sized companies (SME) as: (a) micro companies (less than 10

employees, annual turnover less than 2 million €, annual balance sheet total less than 2 million €), (b) small

companies (11-50 employees, annual turnover 2-10 million €, annual balance sheet total 2-10 million €), (c)

medium companies (51-250 employees, annual turnover 10-50 million €, annual balance sheet total 10-43

million €). Other companies are classified as large (more than 250 employees, annual turnover more than 50

million €, annual balance sheet total more than 43 million €). Thailand by Institute for Small and Medium

Enterprises Development defines SMEs as firms with 15 – 200 employees and 30 – 200 million baht (Thailand

currency) in fixed assets (depending on the business sector), other companies classified as large. We use

subdivision of large companies from EU classification into: (a) large (251-1000 employees, annual turnover 50-

200 million €, annual balance sheet total 43-200 million €) and (b) very large (more than 1000 employees,

annual turnover more than 200 million €, annual balance sheet total more than 200 million €).

14

- YOUNGi is age of CFO of the company i (i = 1, 2…n) ranging from less than 40 years to

more than 60 years (for less than 50 years CFO is defined as YOUNG, for more than 50

years CFO is defined as OLD);

- HEDUi is education of CFO of the company i (i = 1, 2…n) in business/economics ranging

from less than bachelor to higher than postgraduate (if CFO had master’s degree or higher

in business/economics he/she is defined as highly educated – HEDU, in other case he/she

is defined as not highly educated – NHEDU);

- STENi is number of years CFO had been CFO in the company i (i = 1, 2…n) ranging from

less than 4 years to more than 9 years (if CFO is in the position for less than 9 years he/she

is defined as having short tenure – STEN, if CFO is in the position more than 9 years

he/she is defined as having long tenure – LTEN);

- LCAPEXi is the magnitude of capital expenditure budget of the company i (i = 1, 2…n)

ranging from less than 0,1 million € to more than 50 million € (if capital expenditure

budget is up to 1 million € it is defined as small – SCAPEX, if the capital expenditure

budget is more than 1 million € it is defined as large – LCAPEX).

4. Research results and discussion

4.1. Demographic data and descriptive statistics

Data collections for Poland and Thailand started in September 2014 and ended at the

beginning of 2015. Financial data and relevant information of both Polish and Thai companies

were based on their current status at the end of 2013. The descriptive analysis of the total of

327 firms isillustrated in Table 2, separated by countries. From Polish respondents, majority

of the sample was private companies (74%), classified by industry types as manufacturing

(24%) and service (21%). Financial resources of Polish firms were from domestic and

overseas (52% and 48%), top three managers of the firms held usually (51%) less than 5% of

the firm’s equity. About half (47%) of the Polish companies have been established for more

than 20 years and were large in size with more than 250 employees (53%), annual turnover

more than 50 million € (42%), and total assets more than 43 million € (38%).

From Thai respondents, majority of the sample are private companies (76%) and are in

manufacturing industry (56%) and agriculture industry (13%). Unlike the Polish companies,

Thai respondents highly gained capital from domestic market (95%) rather than overseas and

top three managers of Thai firms held usually (58%) less than 5% of the firm’s equity (pretty

much the same as in Polish firms).However, when comparing the number of years the firms

15

are established, the Thai firms were in business less than 10 years (76%) and source of

finance of Thai firms is mostly (95%) domestics and sales mostly domestic (83%). Most of

the Thai firms (95%) were small and medium sized with less than 250 employees, annual

turnover less than 50 million € (96%), and total assets less than 43 million € (97%). The sizes

of Polish and Thai firms were different, majority of Polish firms were large while Thai firms

were small and medium sized. We also see higher proportion of Thai firms paying dividends

in 2013 (67%), while this proportion for Polish firms was only 40%. See Table 2.

Table 2.Companiesdemographics

Type of main activity Poland Thailand

Number % Number %

Sector:

private company 74 69% 168 76%

public company 33 31% 52 24%

Type of main operation:

non-manufacturing 66 62% 176 80%

manufacturing 41 38% 44 20%

Type of main industry classification:

agriculture, forestry, fishing 9 8% 28 13%

mining 1 1% 8 4%

construction 7 7% 6 3%

manufacturing 26 24% 124 56%

transportation and public utilities 9 8% 6 3%

wholesale trade 8 7% 2 1%

retail trade 10 9% 18 8%

finance, insurance, real estate 12 11% 18 8%

services 22 21% 10 5%

public administration 3 3% 0 0%

Origin of capital:

100% domestic 56 52% 210 95%

share of foreign 51 48% 10 5%

Equity owned by the company’s three top managers:

less than 5% 55 51% 128 58%

5-10% 4 4% 36 16%

11-20% 3 3% 4 2%

more than 20% 45 42% 52 24%

Years Company is in operation:

< 2 0 0% 32 15%

2- 5 years 9 8% 68 31%

5-10 years 17 16% 66 30%

10-20 years 31 29% 32 15%

16

Type of main activity Poland Thailand

Number % Number %

> 20 years 50 47% 22 10%

Employees:

< 10 4 4% 24 11%

11-50 17 16% 130 59%

51-250 29 27% 54 25%

251-1000 24 22% 10 5%

> 1000 33 31% 2 1%

Annual turnover (for 2013):

< 2 million € 10 9% 144 65%

2-10 million € 24 22% 56 25%

10-50 million € 28 26% 14 6%

50-200 million € 19 18% 4 2%

> 200 million € 26 24% 2 1%

Total assets (end of 2013):

< 2 million € 23 21% 136 62%

2-10 million € 24 22% 50 23%

10-43 million € 19 18% 26 12%

43-200 million € 18 17% 6 3%

> 200 million € 23 21% 2 1%

Share of total sales abroad:

0% 41 38% 182 83%

1-25% 29 27% 32 15%

25-50% 17 16% 2 1%

> 50% 20 19% 4 2%

Leverage (total debt to asset ratio) (end of 2013):

less than 10% 45 42% 38 17%

10-25% 18 17% 122 55%

25-50% 26 24% 48 22%

> 50% 18 17% 12 5%

Dividend payment (in 2013):

not paying 64 60% 72 33%

paying 43 40% 148 67%

CFO’s characteristics of Thai and Polish firms were quite similaras far as education is

concerned – usually education obtained in business/economics by Polish and Thai CFO’s was

master’s degree (65% for Polish and 77% for Thai), differences can be noted in other

characteristics. The majority of Thai CFO’s were younger than that Polish (50% of Thai

respondents were< 40 years of age, 45% of Polish respondents were 40 – 50 years). With a

younger age, Thai CFO’s worked as a CFO for less than 4 years (77%) while most Polish

17

CFO’s had longer experience. One of the points to be noted is that Polish firms have larger

annual capital expenditure budget than Thai’s. This is because the size of the majority of the

Polish firmswas large while the size of the Thai wassmall and medium. See Table 3.

Table 3.CFO’s and CAPEX demographics

Type of main activity Poland Thailand

Number % Number %

CFO’s age:

< 40 years 36 34% 110 50%

40-50 years 48 45% 92 42%

51-60 years 22 21% 16 7%

> 60 years 1 1% 2 1%

CFO’s academic degree in business/economics:

less than bachelor 6 6% 6 3%

bachelor 3 3% 42 19%

master's degree 70 67% 170 77%

higher than post-graduate (e.g. PhD) 25 24% 2 1%

CFO has been sitting on the Board in Company:

less than 4 years 39 36% 170 77%

4-9 years 42 39% 31 14%

more than 9 years 26 24% 19 9%

The annual capital budget in Your Company:

< 0,1 million € 16 15% 122 55%

0,1-1 million € 41 38% 48 22%

1-10 million € 27 25% 28 13%

10-50 million € 10 9% 20 9%

> 50 million € 13 12% 2 1%

The correlation between independent variables used in the theoretical model was

investigated and the results are presented in Table 4. The results show the predictive ability of

the independent variables that a coefficient of +1.0, a perfect positive correlation, on some

changes in the variables will result in an identical change in another independent, of -1.0, a

perfect negative correlation, will also result in an identical change in such variables but in the

opposite direction and of 0.0, no relationship between the two variables and that the change in

one variable will have no effect in related variables. If the coefficient is a positive number,

then the dependent variable will move in the same direction as the independent variable; if the

coefficient is negative, then the dependent variable will move in the opposite direction of the

independent variable. The highlighted cells on Table 4 illustrate that correlation of

independent variables for both Poland and Thailand. The highlighed cells indicate the higher

18

signifacant at 0.05 and 0.01 level and the upper cells of such highlights show the degree of the

coefficient of such correlation. We can determine the predictive ability of an indicator and to

determine the correlation between two variables.

The variations in firm characteristics (PUB, MAN, FOWN, MAOWN, LSIZE, FSALES,

HLEV, DIV), chief financial officer characteristics (YOUNG, HEDU, STEN) and capital

expenditure size (LCAPEX), permit a rich description of capital budgeting practice in

companies operating in Poland and Thailand, and what is more, allow to analyze if and which

corporate practices are consistent with research results in other countries (e.g. Warfield et al.,

1995; Pike, 1996; Klassen, 1997; Arnold, Hatzopoulos, 2000; Graham, Harvey, 2001; Anand,

2002; Sandahl,Sjögren, 2003; Brounenet al., 2004; Verbeeten, 2006; Hermes,Smid, 2007;

Leon et al., 2008; Truong et al., 2008; Holmen,Pramborg, 2009; Vermaet al., 2009;

Bennounaet al., 2010; Andoret al., 2011; Hartwig, 2012; Ahmed, 2013; Daunfeldt,Hartwig,

2011).

The study surveyed the capital budgeting methods used by Polish and Thai firms. The

respondents were asked whether they used such capital budgeting methods in their decision

making on investment and how often. The data for the comparison between Polish and Thai

firms is shown below. The scores of how often each method was used range from 1 to 5

where score of 1 was used to denote that the CFO has ‘never’ used such method, the score of

2 was ‘rarely, the score of 3 was ‘occasionally’, the score of 4 was often and the score of 5

was always. See Table 5.

19

Table 4.Correlations of independent variables: Poland and Thailand

PUB MAN FOWN MANOWN LSIZE FSALES HLEV DIV YOUNG HEDV STEN LCAPEX

PUB Pearson Correlation 1 .030 -.015 -.056 .331** -.073 .244** .146** .359** .082 .016 .193**

Sig. (2-tailed)

.585 .782 .312 .000 .186 .000 .008 .000 .139 .778 .000

MAN Pearson Correlation .030 1 .182** .086 .269** .408** .060 .019 .035 .071 .045 .199**

Sig. (2-tailed) .585

.001 .122 .000 .000 .283 .730 .533 .201 .422 .000

FOWN Pearson Correlation -.015 .182** 1 -.008 .349** .421** -.030 -.201** .178** .222** .245** .302**

Sig. (2-tailed) .782 .001

.885 .000 .000 .584 .000 .001 .000 .000 .000

MANOWN Pearson Correlation -.056 .086 -.008 1 .044 .225** -.020 -.119* .288** -.287** .410** .329**

Sig. (2-tailed) .312 .122 .885

.424 .000 .721 .031 .000 .000 .000 .000

LSIZE Pearson Correlation .331** .269** .349** .044 1 .440** .219** -.037 .312** .271** .291** .590**

Sig. (2-tailed) .000 .000 .000 .424

.000 .000 .509 .000 .000 .000 .000

FSALES Pearson Correlation -.073 .408** .421** .225** .440** 1 -.006 -.144** .170** .010 .262** .316**

Sig. (2-tailed) .186 .000 .000 .000 .000

.910 .009 .002 .858 .000 .000

HLEV Pearson Correlation .244** .060 -.030 -.020 .219** -.006 1 .070 .042 .127* -.072 .059

Sig. (2-tailed) .000 .283 .584 .721 .000 .910

.208 .445 .021 .196 .285

DIV Pearson Correlation .146** .019 -.201** -.119* -.037 -.144** .070 1 -.100 .099 -.164** -.020

Sig. (2-tailed) .008 .730 .000 .031 .509 .009 .208

.071 .073 .003 .713

YOUNG Pearson Correlation .359** .035 .178** .288** .312** .170** .042 -.100 1 -.174** .523** .339**

Sig. (2-tailed) .000 .533 .001 .000 .000 .002 .445 .071

.002 .000 .000

HEDV Pearson Correlation .082 .071 .222** -.287** .271** .010 .127* .099 -.174** 1 -.149** .048

Sig. (2-tailed) .139 .201 .000 .000 .000 .858 .021 .073 .002

.007 .389

STEN Pearson Correlation .016 .045 .245** .410** .291** .262** -.072 -.164** .523** -.149** 1 .405**

Sig. (2-tailed) .778 .422 .000 .000 .000 .000 .196 .003 .000 .007

.000

LCAPEX Pearson Correlation .193** .199** .302** .329** .590** .316** .059 -.020 .339** .048 .405** 1

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .285 .713 .000 .389 .000

** Correlation is significant at the 0.01 level (2-tailed). * Correlation is significant at the 0.05 level (2-tailed).

20

Table 5.Proportion of companies that use each capital budgeting method

Poland Thailand

never rarely occasionnally often always never rarely occasionnally often always

FORMAL_APR N 5 12 9 18 63 98 40 50 18 14

% 4.70 11.20 8.40 16.80 58.90 44.50 18.20 22.70 8.20 6.40

AUD_DUR_IMPLEMENT N 10 11 20 33 33 14 124 46 30 6

% 9.30 10.30 18.70 30.80 30.80 6.40 56.40 20.90 13.60 2.70

AUD_POST_INVEST N 19 24 13 27 24 110 54 14 30 12

% 17.80 22.40 12.10 25.20 22.40 50.00 24.50 6.40 13.60 5.50

APR_NPV N 26 14 10 24 33 100 12 34 24 50

% 24.30 13.10 9.30 22.40 30.80 45.50 5.50 15.50 10.90 22.70

APR_IRR N 21 8 13 27 38 120 6 14 26 54

% 19.60 7.50 12.10 25.20 35.50 54.50 2.70 6.40 11.80 24.50

APR_PB N 26 6 14 27 34 164 2 16 32 6

% 24.30 5.60 13.10% 25.20 31.80 74.50 0.90 7.30 14.50 2.70

APR_DPB N 41 20 14 14 18 124 12 22 14 48

% 38.30 18.70 13.10 13.10 16.80 56.40 5.50 10.00 6.40 21.80

APR_ARR N 51 17 17 13 9 146 32 12 24 6

% 47.70 15.90 15.90 12.10 8.40 66.40 14.50 5.50 10.90 2.70

COST_WACC N 42 11 8 19 27 128 14 20 56 2

% 39.30 10.30 7.50 17.80 25.20 58.20 6.40 9.10 25.50 0.90

A_SENSITIVITY N 37 11 19 29 11 116 12 44 42 6

% 34.60 10.30 17.80 27.10 10.30 52.70 5.50 20.00 19.10 2.70

A_SCENARIO N 26 11 20 28 22 120 20 42 26 12

% 24.30 10.30 18.70 26.20 20.60 54.50 9.10 19.10 11.80 5.50

21

The results presented in Table 5 show main facts on capital budgeting methods use in

Polish and Thai companies, these are as follows:

formalization of investment appraisal before, during and after investmants are made is

done by more than 50% of Polish and less than 20% of Thai companies,

IRR and NPV are the most popular investment appraisal methods; IRR is used by 60.7% of

Polish and 36.3% of Thai companies and NPV by 53.2% and 33.6% respectively,

majority of companies both in Poland and Thailand do not use WACC for DCF

calculations; WACC is used by 43.0% of Polish and 26.4% of Thai companies,

risc assessment methods are used by less than 50% of Polish companies and about 20% of

Thai firms.

The obtained results as far as diffusion of CBM is concerned are similar to previous

research in Poland (Wnuk-Pel, 20011; Andoret al., 2011; Wnuk-Pel, 2013) and in Thailand

(Rajatanavin, Venkatesh, 2007; Olufemi, Adegbola, 2013; Champathed, Chansa-ngavej,

2015). It also means that the diffusion of capital budgeting methods in Poland and Thailand is

lesser than in more developed countries (Graham, Harvey, 2001; Ryan, Ryan, 2002; Sandahl,

Sjögren, 2003; Brounenet al., 2004; Hermes, Smid, 2007; Truong et al., 2008; Daunfeldt,

Hartwig, 2011).

The results from table 5 are contrary to Hypothesis 4.From this preliminary analysis it

seems that Polish companies use CBM more often that Thai ones. Further analysis is needed

however to adjust the results for company characteristics, chief financial officer

characteristics and magnitude of capital expenditure budget as it seems (Table 2) that

companies in both samples are different.

The correlation between dependent variables used in the theoretical model was investigated

and the results are presented in Table 6.

22

Table 6.Correlations of dependent variables: Poland and Thailand

1 2 3 4 5 6 7 8 9 13 14

FORMAL_APR Pearson Correlation 1 .756** .687** .638** .699** .659** .483** .371** .547** .552** .664**

Sig. (2-tailed)

.000 .000 .000 .000 .000 .000 .000 .000 .000 .000

AUD_DUR_IMPLEMENT Pearson Correlation .756** 1 .706** .584** .646** .601** .516** .378** .539** .608** .609**

Sig. (2-tailed) .000

.000 .000 .000 .000 .000 .000 .000 .000 .000

AUD_POST_INVEST Pearson Correlation .687** .706** 1 .490** .580** .697** .493** .589** .481** .611** .694**

Sig. (2-tailed) .000 .000

.000 .000 .000 .000 .000 .000 .000 .000

APR_NPV Pearson Correlation .638** .584** .490** 1 .838** .383** .736** .193** .738** .673** .540**

Sig. (2-tailed) .000 .000 .000

.000 .000 .000 .000 .000 .000 .000

APR_IRR Pearson Correlation .699** .646** .580** .838** 1 .527** .818** .310** .789** .713** .633**

Sig. (2-tailed) .000 .000 .000 .000

.000 .000 .000 .000 .000 .000

APR_PB Pearson Correlation .659** .601** .697** .383** .527** 1 .349** .635** .366** .485** .677**

Sig. (2-tailed) .000 .000 .000 .000 .000

.000 .000 .000 .000 .000

APR_DPB Pearson Correlation .483** .516** .493** .736** .818** .349** 1 .316** .686** .627** .475**

Sig. (2-tailed) .000 .000 .000 .000 .000 .000

.000 .000 .000 .000

APR_ARR Pearson Correlation .371** .378** .589** .193** .310** .635** .316** 1 .283** .361** .474**

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000

.000 .000 .000

COST_WACC Pearson Correlation .547** .539** .481** .738** .789** .366** .686** .283** 1 .652** .540**

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000

.000 .000

A_SENSITIVITY Pearson Correlation .552** .608** .611** .673** .713** .485** .627** .361** .652** 1 .711**

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000

.000

A_SCENARIO Pearson Correlation .664** .609** .694** .540** .633** .677** .475** .474** .540** .711** 1

Sig. (2-tailed) .000 .000 .000 .000 .000 .000 .000 .000 .000 .000

** Correlation is significant at the 0.01 level (2-tailed).

* Correlation is significant at the 0.05 level (2-tailed).

23

Table 6 illustrate the correlation of dependent variables for Polish and Thai data (n = 327).

The individual capital budgeting method masures (11 variables) are presented to show, in

particular, their correlation with the composite method.Most of the dependent variables are

statistically significant either on 0.05 or 0.01 level. The research shows that that it is

especially the case for DCF methods. NPV, IRR and DPB are positively and significantly

associated with each other (especially NPV and IRR with ρ = 0.838 at the p < 0.01 level (two-

tailed)) which means that the companies use DCF methods together. Companies in Poland

and Thailand do not use only DCF methods, but also PB and ARR, often together with

discounted cash flow techniques which support previous research results (e.g. Hartwig, 2012).

4.2. Factors influencing selection of capital budgeting methods

Table 7 illustrates statistical analysis ofthe factors influencing a selection of capital

budgeting methods (CBM). In our first hypothesis, we test whether company characteristics

(i.e., the type of ownership (PUB), the activities of the company (MAN) etc.) influence the

use of CBM. Our results show that lised and non-listed companiesapply CBM differently.

The results assert what were claimed by Brounenet al. (2004), Anand (2002) and Graham and

Harvey (2001). More specifically, the type of ownership influences formalization of

investment appraisal, discounted rates, methods of risk assessment, and the selection of all of

the investment appraisal methods except for PB method. Moreover, the manufacturing

companies and non-manufacturing make a different decision when selecting formalization of

investment appraisal and methods of risk assessment. The resultssupport the research by

Daunfeldt and Hartwig (2011). However, the type of the activity has no effect on selectionof

two investment appraisal methods, which are DPB and ARR. The foreign ownership of the

company (FOWN) has a significant effect on choosing a formalization of investment

appraisal, investment appraisal methods, discount rates, and methods of risk assessment. The

results support what were revealed by many researchers such as Graham and Harvey (2001),

Ryan and Ryan (2002), Hermes et al. (2007) and Truong et al. (2008). It is apparent that the

management ownership (MAN-OWN), the size (LSIZE), the proportion of sales aborad

(FSALES), the total debt to total asset ratio (HLEV) affect the way in which the companies

chooseCBM, namely formalization of investment appraisal, investment appraisal methods,

discount rates, and methods of risk assessment.The results support the previous studies done

by Warfield et al. (1995),Klassen (1997), Pike (1996), Payne et al.(1999), Graham and

Harvey (2001),Daunfeldt and Hartwig (2011) and the like. Regarding the dividend policy

(DIV), it can be concluded that companies with dissimilar dividend policies select CBMin a

24

different way, as confirmed by the study of Daunfeldt and Hartwig (2011). However, among

the companies with different dividend policy, there is no difference on selecting NPV, IRR,

DPB as an investment appraisal method.

Our second hypothesis is to investigate whether the characteristics of CFOs have an

influence on applying CBM.The results show that age of CFOs (YOUNG) has an influence

on applying a formalization of investment appraisal, investment appraisal methods, discount

rates and methods of risk assessment. The results of our study support the studies of Hermes

et al. (2007) and Daunfeldt and Hartwig (2011). The education of the CFOs(HEDU)has a

significant influence on the way in which the companies choose CBM. It is worth to note that

the result is contradicted from what was claimed by Anandat el.(2002) that CFOs with higher

education use sensitivity analysis more often than CFOs with lower education. The study of

Daunfeldt and Hartwig (2011) stated that CFOs with long tenure and CFOs with short tenure

tend to select CBM in a different way. Our results confirm that the tenure of the CFOs,

(STEN) has a significant effect on the way in which companies choose a formalization of

investment appraisal, investment appraisal methods, discount rate used in DCF methods and

methods of risk assessment.

The third hypothsis is whether companies with large capital expenditure budget useCBM

differently. The results affirm that the size of CAPEX budget (LCAPEX) has a significant

influence on the ways in which the company chooses a formalization of investment appraisal,

investment appraisal methods, discount rate used in DCF methods and methods of risk

assessment.

25

Table 7.The use of capital budgeting in both Poland and Thailand

Country PUB MAN FOWN

MAN

-OWN LSIZE FSALES HLEV DIV YOUNG HEDV STEN LCAPEX

Test MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

MW U

Test

Formalization of investment appraisal

FORMAL_APR .000* .000* .000* .000* .000* .000* .000* .000* .001* .000* .000* .000* .000*

AUD_DUR_IMPLEMENT .000* .000* .002* .000* .000* .000* .000* .000* .039* .000* .002* .000* .000*

AUD_POST_INVEST .000* .000* .000* .000* .000* .000* .000* .000 .002* .000* .000* .000* .000*

Investment appraisal method

APR_NPV .001* .000* .000* .004* .000* .000* .000* .000* .972 .000* .016* .000* .000*

APR_IRR .000* .000* .014* .000* .000* .000* .000* .000* .680 .000* .002* .000* .000*

APR_PB .000* .973 .000* .000* .000* .000* .000* .000* .005* .000* .000* .000* .000*

APR_DPB .088 .000* .059 .016* .000* .000* .001* .000* .699 .000* .004* .000* .000*

APR_ARR .001* .017* .314 .046* .000* .000* .000* .000 .029* .001* .000* .000* .000*

Discount rate used in DCF methods

COST_WACC .000* .000* .066 .000* .000* .000* .000* .000* .629 .000* .024* .000* .000*

Methods of risk assessment

A_SENSITIVITY .001* .000* .009* .004* .000* .000* .000* .000* .761 .000* .107 .000* .000*

A_SCENARIO .000* .000* .003* .000* .000* .000* .000* .000* .008* .000* .000* .000* .000*

26

4.3. Verification of theoretical model

After examining the use of CBM in Poland and Thailand in Table 7, it appeared that

country (Poland and Thailand) did effect the use of capital budgeting methods selection so

further investigation was done on individual countries. Samples on Poland and Thailand were

taken into consideration to assess the relative effects of individual predictors which will also

enable to examine the model with the use of multiple requession equations. A squared

multiple correlation (R2), and an adjusted squared multiple correlation (R

2adj) were calculated

as both indices assess how well the combination of predictor variables in the regression

analysis predicts the criterion variables. As the attempt was made to reach conclusions about

the relative importance of variables in predicting a criterion, the results shown in Table 8.1

illustrate the Polish data’s analysis and 8.2 the Thai data’s analysis.

Polish data’s analysis (see Table 8.1) present how well capital budgeting method selection

is predicted by firm’s characteristics, CFO’s characteristics and magnitude of capital

expenditure budget. In line with previous studies (Pike, 1996; Payne et al., 1999; Graham,

Harvey, 2001; Sandahl,Sjögren, 2003; Brounenet al., 2004; Verbeeten, 2006; Hermes et al.,

2007; Bennounaet al., 2010; Andoret al., 2011; Daunfeldt,Hartwig, 2011; Correia, 2012;

Hartwig, 2012; Ahmed, 2013), size is a significant determinant of the use of CBM, size

significantly influences use of NPV, IRR, WACC and sensitivity analysis. In the case of other

capital budgeting methods (except scenario analysis) size also influences their use but

relationships are not statistically significant. As other companie’s characteristics are

concerned foreign sales influence the use of capital budgeting methods but the relationships

are not statistically significant (it confirmes the results of Hermes et al. 2007; Holmen,

Pramborg, 2009; Daunfeldt,Hartwig, 2011). Also public ownership influences the choice of

most CBM (with the exception of post investment audit and payback period) but the

relationships are not statistically significant (it is in line with Graham, Harvey, 2001; Anand,

2002; Brounenet al. 2004). For other firm’s characteristics (manufacturing activity, foreign

ownership, management ownership, high leverage and dividend payment) the relationships

are hovewer not significant statistically.

As CFO’s characteristics are concerned the results from Polish companies suggest (in line

of the previous research, e.g. Anand, 2002; Hermes et al. 2007; Leon et al. 2008; Ahmed,

2013) that high education ofCFO’s influences most (except accounting rate of return) of the

CBM methods use although therelations are not statistically significant. For other CFO’s

characteristics (young age and short tenure) the relationships are statistically insignificant

(contradictory with the expectations). Size of capital expenditure budget, in line with previous

27

studies (Hermes et al. 2007; Vermaet al. 2009; Correia, 2012) also proved to influence on the

use of capital budgeting methods although the relation is significant only for NPV use.

Table 8.1 also shows the percentage of the capital budgeting methods variation that is

explained by company characteristics, CFO characteristics and size of capital expenditure

budget. Models based on the data from Polish companies do not explain the variability of

dependent variables satisfactory, the best fit could be observed in the case of NPV and IRR.

NPV use is in 37.3% explained by the model and IRR use in 32.3%. In the case of NPV

explanation only two independent variables are statistically significant – company size

(0.471) and size of campany’s capital expenditure budget (0.365). In the case of IRR

explanation only one independent variable is significant – company size (0.360). The use of

WACC, sensitivity analysis and scenario analysis are explained respectively in 23.1%, 22.2%

and 20.3%. Other dependent variables are explained by the model in less than 20%.

28

Table 8.1.An analysis of the use of capital budgeting: Poland

R2

Adj.

R2

Std. Error of

the Estimate Constant PUB MAN FOWN

MAN-

OWN LSIZE FSALES HLEV DIV YOUNG HEDV STEN

LCA-

PEX

FORMAL_APR .137 .027 1.223 2.166 .259 .027 -.020 -.129 .023 .120 .072 .057 .030 .174 .106 .208

Significant .039 .404 .925 .943 .184 .854 .384 .509 .836 .869 .330 .546 .108

AUD_DUR_IMPLEMENT .150 .041 1.250 1.904 .079 -.399 .373 -.012 .150 .161 .025 -.119 .129 .100 -.069 .172

Significant .075 .804 .172 .190 .902 .244 .251 .822 .670 .486 .585 .698 .192

AUD_POST_INVEST .140 .030 1.423 2.410 -.085 .175 .007 -.070 .120 .113 -.243 -.374 .119 .108 .082 .147

Significant .048 .815 .597 .983 .532 .412 .481 .058 .242 .574 .603 .689 .326

APR_NPV .373 .293 1.339 -.110 .327 -.053 -.206 -.038 .471 .031 -.013 -.119 .021 .315 -.101 .365

Significant .923 .335 .865 .497 .718 .001 .839 .916 .690 .917 .109 .600 .011

APR_IRR .323 .236 1.328 .813 .295 -.559 -.118 -.169 .360 .229 .104 .085 -.163 .217 .272 .235

Significant .471 .382 .073 .695 .110 .010 .126 .379 .775 .410 .264 .155 .095

APR_PB .179 .074 1.508 .506 -.109 .047 .098 .036 .232 -.054 -.013 .451 .224 .018 .100 .263

Significant .692 .776 .894 .775 .763 .137 .749 .926 .183 .317 .936 .642 .099

APR_DPB .182 .077 1.460 .795 .399 -.163 .145 -.029 .241 -.066 .049 -.447 -.035 .142 -.085 .321

Significant .521 .282 .631 .662 .798 .109 .689 .708 .173 .871 .506 .685 .039

APR_ARR .058 -.062 1.407 2.230 .135 -.340 -.092 .083 .188 .128 -.032 -.187 .046 -.156 .041 -.041

Significant .064 .705 .300 .773 .457 .195 .417 .802 .553 .827 .446 .839 .780

COST_WACC .231 .133 1.571 .492 .584 -.784 .431 .073 .500 .046 .183 -.194 -.279 .019 -.015 .108

Significant .712 .144 .034 .228 .555 .002 .793 .193 .581 .234 .933 .946 .515

A_SENSITIVITY .222 .123 1.353 .394 .054 -.091 -.191 -.036 .313 .120 -.027 -.056 -.057 .166 .214 .242

Significant .731 .874 .773 .533 .738 .026 .429 .822 .854 .778 .400 .272 .092

A_SCENARIO .203 .101 1.398 .489 .621 -.204 .163 -.045 -.027 .228 .002 -.263 -.383 .570 .089 .247

Significant .680 .081 .531 .606 .686 .852 .147 .990 .401 .067 .006 .656 .095

29

Table 8.2.An analysis of the use of capital budgeting: Thailand

R2 Adj.

R2

Std. Error of

the Estimate Constant PUB MAN FOWN

MAN-

OWN LSIZE FSALES HLEV DIV YOUNG HEDV STEN

LCA-

PEX

FORMAL_APR .623 .601 .789 .619 1.541 .131 -.671 .288 -.291 .480 -.349 -.279 .105 .051 -.017 .342

Significant .349 .000 .372 .018 .001 .014 .000 .000 .020 .414 .753 .898 .000

AUD_DUR_IMPLEMENT .532 .505 .636 .904 1.097 .132 -.848 .239 -.168 .606 -.316 -.082 .147 .274 -.098 .061

Significant .090 .000 .265 .000 .000 .077 .000 .000 .391 .158 .037 .350 .390

AUD_POST_INVEST .705 .688 .708 -.400 .483 .219 -.088 .449 -.052 .436 -.386 -.046 .317 .106 .011 .256

Significant .499 .005 .096 .727 .000 .624 .000 .000 .665 .007 .463 .923 .001

APR_NPV .709 .692 .919 -1.744 2.567 .498 -.666 .246 .228 .308 -.334 -.322 .414 .188 -.108 .074

Significant .024 .000 .004 .044 .012 .097 .024 .004 .021 .006 .318 .474 .466

APR_IRR .884 .877 .613 -2.829 3.325 .203 -.983 .622 .182 .311 -.330 -.235 .007 .286 .280 -.027

Significant .000 .000 .075 .000 .000 .048 .001 .000 .012 .944 .024 .006 .689

APR_PB .801 .790 .573 -1.233 -.290 .128 .664 .597 -.207 .396 -.275 -.080 .027 .424 .251 .264

Significant .011 .037 .230 .001 .000 .016 .000 .000 .355 .770 .000 .008 .000

APR_DPB .869 .862 .621 -2.123 3.281 .116 -.699 .242 .285 .263 -.604 -.006 .344 .011 .327 -.081

Significant .000 .000 .316 .002 .000 .002 .005 .000 .950 .001 .933 .002 .239

APR_ARR .741 .727 .599 .681 -.226 .014 .125 .574 .015 .121 -.521 .168 -.061 .140 .285 .023

Significant .175 .119 .899 .558 .000 .867 .172 .000 .063 .534 .254 .004 .727

COST_WACC .846 .837 .539 -1.178 2.173 .159 -.467 .116 .545 .390 -.546 -.013 .039 -.142 .179 .114

Significant .010 .000 .112 .016 .043 .000 .000 .000 .871 .657 .198 .045 .058

A_SENSITIVITY .748 .733 .679 -1.999 1.877 .031 -.902 .500 -.068 .464 -.394 -.074 .347 .580 .114 .014

Significant .001 .000 .808 .000 .000 .502 .000 .000 .466 .002 .000 .306 .853

A_SCENARIO .774 .761 .639 -.569 .984 .185 -.485 .481 -.085 .313 -.390 -.130 .168 .189 .218 .315

Significant .287 .000 .119 .035 .000 .370 .001 .000 .176 .109 .150 .039 .000

30

For Thai data’s analysis (see Table 8.2), we see that there are very far different from the

Polish data’s analysis (see Table 8.1). The first formalization of investment appraisal, formal

evaluation before investment decision, was mostly influenced by the type of ownership of the

company (PUB– listed on stock exchange, PRIV–private) with a highest coefficient of 1.541

and statistical significance (p = 0.01), and every other company’s characteristics except the

activity type of the company (manufacturing or not). The variable correlation is 62.3%, R2=

0.623, adjusted R2 = 0.601, F (12, 207) = 28.539, p<0.01. The CFO’s characteristics do not

determine this method’s selection, while the size of the capital expenditure budget determines

formal evaluation before the investment decision.

Monitoring investments during implementation is influenced bycompany’s characteristics

similarly to the formal evaluation before investment decision; type of ownership of the

company has a highest coefficient of 1.097 and is statistically significant (p<0.01), only

dividend policy of the company does not correlate to this method selection. When considering

the CFO’scharacteristic’s, the education of the CFO determines this method selection, but not

the size of the capital budget. The independent variables then accounted for the selection of

the CBM methods significantly 53.2%, R2= 0.532, adjusted R

2 = 0.505, F (12, 207) = 19.621,

p<0.01.

The implemenatation on post-investment audit method is influenced by company’s

characteristics similar to the previous CBM method selection. The shares owned by top three

managers and the type of ownership of the company determine this method use. The only

difference is on the factor of foreign ownership of the company that does not determine the

method selection. Young CFO and also the size of the capital expenditure budget

arefactorsdetermining post-investment adudituse . The correlation of the independent

variables can then predict the adoption of the post-investment audit method selection at 70.5%

which indicates the highest correlation among the formalization appraisal methods where R2=

0.705, adjusted R2 = 0.688, F (12, 207) = 41.321, p<0.01.

Once we consider the variables that influence formalization of investment appraisal

methods selection, we find that four compay’s characteristic factors/variables strongly

influence adoption, theu are:i) the type of ownership (listed company), ii) the larger

proportion of shares owned by top three managers, iii) the higher proportion of foreign sales

and iv) the total debt to asset ratio of the company. We cannot find the common CFO

characteristics that significantly influence the adoption of the formalization appraisal method,

while larger size of capital expenditure budget surely support the adoption of the formal

appraisal method in Thailand.

31

We also investigate the relationship of investment appraisal methods used – NPV, IRR,

PB, DPB, ARR – and independent variables: company characteristics, CFO charactersitics

and the magnitude of the capital expenditure budget. All company characteristics, except for

the size of the company, show statistically significant influence(70.9%)on the selection of

NPV; R2= 0.709, adjusted R

2 = 0.692, F (12, 207) = 41.973, p<0.01. The most important

factor determining the selection of NPV is the type of ownership of the company (listed

companiesuse NPV more often than private companies; coefficient 2.567). The young CFO is

the only CFO’s characteristic’sinfluencing the selection of NPV method, while the size of the

capital expenditure budget does not determine NPV method selection.

The adoption of IRR, PB and DPB are influenced by similar company characteristics

where all company characteristics affect the decision on adoption of those three

aforementioned methods, except for the type of company’s activity. Type of ownership of the

company (listed company) does strongly influence the adoption of the IRR and DPB with the

coefficient of 3.325 and 3.281, but not PB. Higher education and the short tenure also

determine the adoption of IRR and PB, while the adoption of DPB is determind byage and

tenure of the CFO. The magnitude of the capital expenditure affects only the adoption of the

PB method. The regression equation of the selection of IRR indicates that88.4% of the

criterion variance is accounted for by its linear relationship with the independent variables;

R2= 0.884, adjusted R

2 = 0.877, F (12, 207) = 131.446, p<0.01, while PB indicates 80.1%

(R2= 0.801, adjusted R

2 = 0.790, F (12, 207) = 69.519, p<0.01), and DPB indicates 86.9%

(R2= 0.869, adjusted R

2 = 0.862, F (12, 207) = 114.865, p<0.01), respectively.

While most capital budgeting methods selections have several influencing factors, the

selection of accounting rate of return (ARR) have only three influencing factors; the shares of

the company owned by top three managers, the debt to asset ratio, and short tenure of the

CFO. The regression equation of the ARR method selection indicates 74.1% ;R2= 0.741,

adjusted R2 = 0.727, F (12, 207) = 49.478, p<0.01.

Overall, company’s characteristics significantly influence investment appraisal methods

used especially NPV, IRR, PB and DPB. The most influencing CFO’s characteristic’s factor

is the short tenure of the CFO. Interestingly, size of the capital expenditure budget does not

correlate to the selection of any investment appraisal methods, except for that of PB.

As discount rate used in discountedcashflow methods is concerned, we found that type of

ownership (public company) mostly influene the use of WACC withthe coefficient of 2.173.

Other company’s characteristics, except the activity of the company and dividend policy, also

significantly influence the adoption of WACC. The CFO’scharacteristic that correlatewiththe

32

selection of WACC is short tenure, while there is no correlation with size of the capital

expenditure budget. The influencing variables can determine the selection of WACC

in84.6%; R2= 0.846, adjusted R

2 = 0.837, F (12, 207) = 94.531, p<0.01.

The selections of risk assessment methodsisalso determined bycertain company

characteristics.For the selection of sensitivity method, the most influencing factor is the type

of the company ownership (listed company), the coefficient 1.877 illustrates the high

correlation at p <0.01. Other company’s characteristics that influence the selection of

sensitivity analysis are foreign ownership, proportion of shares owned by top three managers,

foreign sales and leverage. The CFO’s characteristics that most influence the use of sensitivity

analysisare young age of CFO and education of CFO, while size of the capital expenditure

budget does not influence the use of this method. Such influencing variables can then

determine the selection of sensitivity method in 74.8%; R2= 0.748, adjusted R

2 = 0.733, F

(12, 207) = 51.108, p<0.01.

The last method that we investigate is the scenario analysis where certain company

characteristics influence this selection of this method in similar way as the sensitivity method

selection. The most influencing factor is the type of the company’s ownership (listed

company) (the coefficient 0.984, p<0.01). Other company’s characteristics that influence the

selection of scenario analysis are foreign ownership, proportion of shares owned by top three

managers, foreign sales and leverage. The selection is also determined by the short tenure of

CFO and size of capital expenditure budget. The regression equation explains influence of

these factors on the selection of this method in 77.4% with R2= 0.774, adjusted R

2 = 0.761, F

(12, 207) = 59.079, p<0.01.

If we consider the factors that influence the adoption of both risk assessment methods, the

most correlated factors are company characteristics. However, considering overall factors that

influence the selection of capital budgeting method as a whole, the authors see that type of

company ownership as listing on stock exchange is the most powerful factor for Thai

companies.

The findings of our results are interesting.As literature in Poland and Thailand on capital

bugeting management is very limited, our results add more value to Polish and Thai literature.

What we found contradicts previous research conducted in Thailand. Rajatanavin and

Venkatesh (2007) concluded in their study that NPV and IRR are two most frequently used

capital budgeting techniques. Payback criterion was also found to be popular among Thai

large firms. This is not the case from our point of view. As hypotheses 4 is concerned, the

statistics on Thai companiesillustrate relatively stronger influence of independent variables on

33

CBM selection than that of Polish companies. Also the diffusion od CBM in Polish and Thai

companies are different. It draws us to the conclusion that researchresults do not support the

fouth hypothesis as the use of capital budgeting methods by Thai and Polish firms is very

different.

5. Conclusions

Using data for companies operating in Poland and Thailand this study examined factors

determining the use of capital budgeting methods and also diffusion of these methods. As the

diffusion of CBM is concerned the research shows their more frequent use in Polish than in

Thai companies (it is evident in the case of formalization of investment appraisal process,

investment appraisal methods use, cost of capital use in DCF calculations and methods of risk

assessment). Particularly NPV was used (often or always) by 53.2% of Polish and 33.6% of

Thai companies whereas IRR was used (often or always) by 60.7% of Polish and 36.3% of

Thai companies – the results for other methods are similar. The correlation analysis between

CBM used showed that companies tend to use a package of different methods, this is

especially evident in the case of DCF methods, companies usually use all of them.

Analysis of the company’s characteristics shows that foreign ownership, management

ownership, large size of the company, foreign sales and high leverage influence the use of

CBM (all independent variables are statistically significant). Also public ownership influence

the use of capital budgeting methods (with exception of PB). Influence on the use of capital

budgeting methods of manufacturing activity and dividend payment was shown for only some

CBM. The research also shows statistically significant influence on the use of capital

budgeting methods of CFO’s characteristics (the only exception was that high CFO’s

education influence on the use of sensitivity analysis is not statistically significant). Also large

size of capital expenditure budget has statistically significant influence on the use of all CBM.

As the results suggest that there are significant differences between countries when using

formal methods of investment appraisal, choosing investment appraisal methods, using

discount rate in DCF methods and also risk assessment methods, the decision was made to run

further investigation on individual countries. The regression analysis showed that in Polish

sample the only independent variables which in statistically significant way influencethe

selection of some CBM are large size of the company (NPV, IRR, WACC and sensitivity

analysis) and large capital expenditure budget (NPV). Other independent variables influence

is not statistically significant. Regression models based on Polish data do not explain the

variability of CBM use satisfactory, the best fit could be observed in the case of NPV (R2 =

34

0.373) and IRR (R2 = 0.323). The use of WACC, sensitivity and scenario analysis are

explained in more then 20% whereas other dependent variables in less than 20%.

Model works much better in the case of Thai companies. As company characteristics are

concerned, public ownership, foreign ownership, managers ownership, large company size,

foreign sales and high leverage influence the use of CBM (it is worth stressing that

contradictory to research hypotheses some ot these relations are negative, especially in the

case of high leverage). The only companies characteristics which do not influence most of

CBM use are manufacturing activity and dividend payment. CFO’s characteristics influence

the use of capital budgeting methods but only part of the relations arestatistically significant,

the same could be observed in the case of CAPEX size. The regression results were much

better in the case of Thai sample. In the case of every CBM the fit is very satisfactory and

ranges from R2 = 0.532 in the case of audit during implementation to R

2 = 0.884 in the case of

IRR. The results obtained prove that the model explains variation in capital budgeting

methods use to a large degree for Thai sample and is much weaker in explaining Polish

results.

The contributionof this research to prior studies is threefold. Firstly the study shows on a

large sample of companies which CBM are used by Polish and Thai companies and how often

they are used, to authors knowledge such a complex study has not been performed in these

countries before. Secondly a broader set of explanatory variables was used including

company’s characteristics, CFO’s characteristics and magnitude of capital expenditure budget

which permited a rich description of campanies practices and allowedanalysys if and which

companies practices are consistent with prior research. Thirdly the study enables comparison

between capital budgeting practices in European and Asian companies and comparing results

with practice in other countries. Authors believe that the research results will be interesting

for academic’s also in other countries and will bridge the gap in management accounting

literature.

Study results could also be useful from a practical point of view. They could especially

help practitioners to identify areas in their companies wher capital budgeting practice is far

from academic recommendations and where implementation of the methods, which are both

theoretically grounded and used in practice of companies in more developed countries, could

possibly be beneficial for their companies due to the fact that they could facilitate activities

which create value. Wider diffusion of CBM in Polish and Thai companies could improve the

effectiveness of investment decisions and positively influence companies effectiveness.

35

The study is limited in several respects. First of all this research measure only the reported

(perceived) use of capital budgeting methods (not necessarily actions but rather beliefs) – one

cannot be sure if and how the methods are actually used. Secondly, as the sample was not

representative for all Polish and Thai companies, the results should be interpreted with

caution. Thirdly there is a possibility of non-response bias in the results obtained, the response

rates are low (especially in Poland), so the results could show responses of people more

familiar with capital budgeting methods (they could overestimate the use of CBM). Fourthly

comparisons between Polish and Thai responses should be especially carefull as the samples

in both countries seem to be different (company size, origin of capital, years in operation

etc.). The last point to be made is that survey research generally do not allow in-depth

analysis of the capital budgeting practice in a way it is possible using case study research.

Comparing practice of Polish and Thai companies with the use of case study method could

enable more detailed analysis of not only CBM used but also examination of the process of

investment selection, appraisal, realization and control. This could be the next step in the

research.Bearing these limitations in mind, however, the research permits a broad

examination of CBM used in Polish and Thai companies, analysis of factors determining their

use and comparisons with similar researches done in other countries.

References:

1. Ahmed I.E., (2013),Factors determining the selection of capital budgeting techniques,

„Journal of Finance and Investment Analysis”, 2(2), pp. 77-88.

2. Anand M. (2002), Corporate Finance Practices in India: A Survey, „Vikalpa”, 2(4), pp.

29-51.

3. Andor G., Mohanty S., Toth T. (2011), Capital budgeting practices: a survey of central

and eastern European firms, Word Bank, January, pp. 1-45.

4. Arnold G., Hatzopoulos P. (2000), The theory-practice gap in capital budgeting:

Evidence from the United Kingdom, „Journal of Business Finance and Accounting”, 27,

pp. 603-626.

5. Bennouna K., Meredith G.G., Marchant T. (2010), Improved capital budgeting decision

making: evidence from Canada, „Management Decision”, 48(2), pp. 225-247.

6. Binder J.J., Chaput J.S. (1996), A positive analysis of corporate capital budgeting

practices, „Review of Quantitative Finance and Accounting”, 6(3), pp. 245-257.

7. Block S. (2005), Are there any differences in capital budgeting procedures

betweenindustries? An empirical study, “The Engineering Economist”, 50, pp. 55-67.

8. Brounen D., De Jong A., Koedijk K. (2004), Corporate finance in Europe: Confronting

theory with practice, „Financial Management”, 33(4), pp. 71-101.

36

9. Burns R.M., Walker J. (2009), Capital budgeting surveys: the future is now, Journal of

Applied Finance, 1&2, pp. 78-90.

10. Champathed, K., &Chansa-ngavej, C. (2012). A contingency model of capital budgeting

decisions in the new economy. International Seminar on Science and Technology

Innovations 2012. Jakarta.

11. Champathed, K., &Chansa-ngavej, C. (2015), Capital Budgeting Practice of Thai Firms,

7(1), 59-66.

12. Correia C. (2012), Capital budgeting practices in South Africa: a review, South African

Journal of Business Management, 43(2), pp. 11-29.

13. Danielson M.G., Scott J.A. (2006), The capital budgeting decisions of small businesses,

“Journal of Applied Finance”, Fall/Winter, pp. 45-56.

14. Daunfeldt S., Hartwig F. (2011), What determines the use of capital budgeting methods?

Evidence from Swedish listed companies, Social Science Research Network, working

paper, pp. 1-37.

15. Graham J., Harvey C. (2001), The theory and practice of corporate finance: Evidence

from the field, „Journal of Financial Economics”, 61, pp. 187-243.

16. Hartwig F. (2012), Four papers on top management’s capital budgeting and accounting

choices in practice, working paper Upsala University, pp. 1-43.

17. Hermes N.P., Smid L.Y. (2007), Capital budgeting practices: a comparative study of the

Nederlands and China, „International Business Review”, 16(5), pp. 630-654.

18. Holmen M., Pramborg B. (2009), Capital budgeting and political risk: empirical

evidence, „Journal of International Financial Management and Accounting”, 20(2), pp.

105-134.

19. Klassen K.J. (1997), The impact of inside ownership concentration on the trade-off

between financial and tax reporting, „The Accounting Review”, 72(3), pp. 455-474.

20. Leon F., Isa M., Kester G. (2008), Capital budgeting practices of listed Indonesian

companies, „Asian Journal of Business and Accounting”, 1(2), pp. 175-192.

21. Liljeblom E., Vaihekoski M. (2004), Investment evaluation methods and required rate of

return in Finnish publicly listed companies, „LTA”, January, pp. 9-24.

22. Miller P., O’Leary T. (2007), Mediating instruments and making markets: Capital

budgeting, science and the economy, “Accounting, Organizations and Society”, 32, pp.

701-734.

23. Olufemi, A. &Adegbola, O. (2013), Current Practice of Corporate Finance in Thailand: A

comparison of SMEs in Thailand and US Companies, Journal of Economics and Finance,

1(2), 26-38.

24. Payne J., Heath W., Gale L. (1999), Comparative financial practice in the USA and

Canada: Capital budgeting and risk assessment techniques, „Financial Practice and

Education”, 9, pp. 16-24.

25. Pike R.H. (1996), A longitudinal study of capital budgeting practices, „Journal of

Business Finance and Accounting”, 23(1), pp. 79-92.

26. Rajatanavin, R., &Venkatesh, S. (2007), CURRENT PRACTICE OF CORPORATE

FINANCE IN THAILAND, http://papers.ssrn.com/sol3/papers.cfm?abstract_id=1009533

37

27. Rogowski W., &Kasiewicz S. (2006). Ocena Opłacalności Inwestycji Społecznych. Bank

iKredyt, 1, 1-12.

28. Ryan P., Ryan G. (2002), Capital budgeting practices of the Fortune 1000: How have

things changed?,„Journal of Business and Management”, 8(4), pp. 355-64.

29. Sandahl G., Sjögren S. (2003), Capital Budgeting Methods among Sweden’s Largest

Groups of Companies. The State of the Art and Comparison with Earlier Studies,

„International Journal of Production Economics”, 84(1), pp. 51-69.

30. Szychta A. (2001), Zastosowanie metod rachunkowości zarządczej w przedsiębiorstwach

w Polsce, „Zeszyty Teoretyczne Rachunkowości”, 61, pp. 101-119.

31. Truong G., Partington G., Peat M. (2008), Cost-of-capital estimation and capital-

budgeting practice in Australia, „Australian Journal of Management”, 33(1), 95-121.

32. Verbeeten F.H.M. (2006), Do organizations adopt sophisticated capital budgeting

practices to deal with uncertainty in the investment decision? A research note,

“Management Accounting Research”, 17, pp. 106-120.

33. Verma S., Gupta S., Batra R. (2009), A survey of capital budgeting practices in corporate

India, „The Journal of Business Perspective”, 13(3), pp. 1-17.

34. Warfield T.D., Wild J.J., Wild K.L. (1995), Managerial ownership, accounting choices,

and informativeness of earnings, „Journal of Accounting and Economics”, 20(1), pp. 61-

91.

35. Wnuk-Pel, T. (2011), Ocena i kontrola opłacalności inwestycji w przedsiębiorstwach w

Polsce – wstępne wyniki badań ankietowych [w:] Rachunkowość, audyt i kontrola w

zarządzaniu (red. Sobańska I., Turzyński M.), Wydawnictwo UŁ, Łódź 2011, pp. 165-

190.

36. Wnuk-Pel, T. (2013), Capital Budgeting Practices in Non-manufacturing Companies in

Poland, “Social Sciences”, 4(82), pp. 59-70.

37. Zarzecki D. (1997). Metody Oceny Efektywności Inwestycji – Wybrane Zagadnienia.

Interbook, Szczecin.

38

APPENDIX 1

QUESTIONNAIRE

I. COMPANY CHARACTERISTICS

1.1. Sector:

private company public company

1 2

1.2. Type of main operation:

non-manufacturing manufacturing

1 2

1.3. Type of main industry classification:

agriculture, forestry, fishing 1

mining 2

construction 3

manufacturing 4

transportation and public utilities 5

wholesale trade 6

retail trade 7

finance, insurance, real estate 8

services 9

public administration 10

1.4. Origin of capital:

100% domestic share of foreign

1 2

1.5. Equity owned by the company's three top managers:

less than 5% 5-10% 10-20% more than 20%

1 2 3 4

1.6. Years Your Company is in operation:

< 2 2- 5 years 5-10 years 10-20 years > 20 years

1 2 3 4 5

1.7. Employees:

< 10 11-50 51-250 251-1000 > 1000

1 2 3 4 5

1.8. Annual turnover (for 2013):

< 2 million € 2-10 million € 10-50 million € 50-200 million € > 200 million €

1 2 3 4 5

1.9. Total assets (end of 2013):

< 2 million € 2-10 million € 10-43 million € 43-200 million € > 200 million €

1 2 3 4 5

1.10. Share of total sales abroad:

0% 1-25% 25-50% > 50%

1 2 3 4

1.11. Leverage (total debt to asset ratio) (end of 2013):

less than 10% 10-25% 25-50% > 50%

1 2 3 4

39

1.12. Dividend payment (in 2013):

not paying paying

0 1

II. CHIEF FINANCIAL OFFICER CHARACTERISTICS

2.1. Chief Financial Officer’s age:

< 40 years 40-50 years 50-60 years > 60 years

1 2 3 4

2.2. Chief Financial Officer’s academic degree in business/economics:

less than bachelor bachelor master's degree higher than post-

graduate (e.g. PhD)

1 2 3 4

2.3. Chief Financial Officer has been sitting on the Board in Your Company:

less than 4 years 4-9 years more than 9 years

1 2 3

III. ORGANIZATION OF INVESTMENT PROCESS

3.1. What is the annual capital budget in Your Company:

< 0,1 million € 0,1-1 million € 1-10 million € 10-50 million € > 50 million €

1 2 3 4 5

3.2. What is the minimal investment requiring formal assessment in Your Company:

< 0,01 million € 0,01-0,1 million € 0,1-0,5 million € 0,5-1 million € > 1 million €

1 2 3 4 5

3.3. At what organizational level in Your Company are investment decisions finally made:

minor

investments

medium-size

investments

major

investments

very large

investments

manager of a department 1 2 3 4

director of a division which 1 2 3 4

company management/headquarters 1 2 3 4

3.4. When investments are evaluated in Your Company:

method never rarely occasio-

nally

often always

formal evaluation is carried out before

investment decision is made

1 2 3 4 5

investment is monitored during

implementation

1 2 3 4 5

post-implementation audit is carried out 1 2 3 4 5

IV. USE OF INVESTMENT APPRAISAL METHODS

4.1. What methods of investment appraisal are used in Your Company (please tick one answer for each raw

only):

method never rarely occasio-

nally

often always

net present value (NPV) 1 2 3 4 5

internal rate of return (IRR) 1 2 3 4 5

payback (PB) 1 2 3 4 5

discounted payback (DPB) 1 2 3 4 5

accounting rate of return (ARR) 1 2 3 4 5

other, i.e…………..….…………… 1 2 3 4 5

40

4.2. Which of the following approaches Your Company use to determine cost of capital (please tick one answer

for each row only):

method never rarely occasio-

nally

often always

weighted average cost of capital 1 2 3 4 5

cost of debt 1 2 3 4 5

cost of equity capital 1 2 3 4 5

an arbitrarily chosen figure 1 2 3 4 5

another rate, i.e…………………………… 1 2 3 4 5

4.3. Which of the following risk assessment methods Your Company use (please tick one answer for each row

only):

method never rarely occasio-

nally

often always

ignore risk 1 2 3 4 5

subjective risk assessment 1 2 3 4 5

sensitivity analysis 1 2 3 4 5

scenario analysis 1 2 3 4 5

other, i.e.……………………………….. 1 2 3 4 5

4.4. Has there been a major switch in capital budgeting methods over the last 5 years in Your Company:

a. no,

b. yes and it included……………………………………………………………………………..………

…………………………………………………………………………………………………………

4.5. Are investment appraisal rules likely to change in Your Company in near future:

c. no, because current methods are appropriate,

d. no, despite the fact that current methods should be replaced by other methods,

e. yes, and the changes will include ……………………………………..……………….………………

…………………………………………………………………………………………….……………

In case You are willing to participate in a short (15-20 minutes) telephone interview on capital budgeting, please

specify:

a. Your name………………………………………………………………………………………………..

b. Your phone number………………………………………………………………………………..………

c. Your e-mail address…………………………………………………………………………………..……