Assignment 3

Applied Economics and Finance

Vol. 3, No. 2; May 2016

ISSN 2332-7294 E-ISSN 2332-7308

Published by Redfame Publishing

URL: http://aef.redfame.com

15

Capital Budgeting Theory and Practice:

A Review and Agenda for Future Research

Lingesiya Kengatharan 1

1 Department of Financial Management, University of Jaffna, Sri Lanka.

Correspondence: Lingesiya Kengatharan, Department of Financial Management, University of Jaffna, Sri Lanka.

Received: December 21, 2015 Accepted: January 14, 2016 Available online: February 4, 2016

doi:10.11114/aef.v3i2.1261 URL: http://dx.doi.org/10.11114/aef.v3i2.1261

Abstract

The main purpose of this research was to delineate unearth lacunae in the extant capital budgeting theory and practice

during the last two decades and ipso facto become springboard for future scholarships. Web of science search and iCat

search were used to locate research papers published during the last twenty years. Four criteria have been applied in

selection of research papers: be an empirical study, published in English language, appeared in peer reviewed journal

and full text research papers. These papers were collected from multiple databases including OneFile (GALE), SciVerse

ScienceDirect (Elsevier), Informa - Taylor & Francis (CrossRef), Wiley (CrossRef), Business (JSTOR), Arts & Sciences

(JSTOR), Proquest ,MEDLINE (NLM), and Wiley Online Library. Search parameters covered capital budgeting,

capital budgeting decision, capital budgeting theory, capital budgeting practices, capital budgeting methods, capital

budgeting models, capital budgeting tools, capital budgeting techniques, capital budgeting process and investment

decision. Thematic text analyses have been explored to analyses them. Recent studies lent credence on the use of more

sophisticated capital budgeting techniques along with many capital budgeting tools for incorporating risk.

Notwithstanding, it drew a distinction between developed and developing countries. Moreover, factors impinging on

choice of capital budgeting practice were identified, and bereft of behavioral finance and event study methodological

approach were highlighted. More extensive studies are imperative to build robust knowledge of capital budgeting theory

and practice in the chaotic environment. This research was well thought out in its design and contributed by stating the

known and unknown arena of capital budgeting during the last two decades. This scholarship facilitates to academics,

practitioners, policy makers, and stakeholders of the company.

Keywords: Capital budgeting theory and practices, capital budgeting tools for incorporating risk, discount rate

1. Introduction

Predominantly, area of capital and capital budgeting of financial management have been attracted many researchers

during the last five decades and the seminal studies culminated with presenting many theories (e.g., Markowitz,1952;

Modigliani & Miller,1958; Markowitz,1959; Miller & Modigliani,1961; Fama,1970; Black & Scholes,1973; Ross, 1976;

Roll,1977; Myers,1977; Myers,1984; Jensen,1986; Ritter,1991;Graham & Harvey, 2001; Myers,2003; Halov &

Heider,2004; Atkeson & Cole,2005;) and models (e.g.,Markowitz,1952; Sharpe,1963; Sharpe,1964; Linter,1965;

Roll,1977) time to time. Notwithstanding, due to the globalization, environmental changes and cutting edge advanced

technological developments, theories and models developed in the past do not applicable today and many of them are

criticized and their applicability in practice is intriguing (e.g., Malkiel, 2003; Bornholt, 2013). A curious instance

illustrated by Brounen, de Jong and Koedijk (2004) is that ‗Nobel Prize winning concepts like the capital asset pricing

model and capital structure theorems have been praised and taught in class rooms, but to what the extent to these

celebrated notions have also found their way into corporate board rooms remains somewhat opaque‘ (p.72). ‗Traditional

capital budgeting methods have been heavily criticized of discouraging the adoption of advanced manufacturing

technology and thus undermining the competitiveness of Western firms‘ (Slagmulder, Bruggeman & Wassenhove, 1995,

p.121). In a similar vein, many research scholars on their seminal scholarships argued that there are gaps in theory of

capital budgeting and its applicability (e.g., Mukheijee & Henderson, 1987; Arnold & Hatzopoulos, 2000; Graham &

Harvey, 2001; Cooper, Morgan, Redman & Smith, 2002; Brounen et al., 2004; Kersyte, 2011).

Firms operating in a dynamic environment must respond to changes to beat competitors and to sustain, survive and

grow in markets (Ghahremani, Aghaie & Abedzadeh, 2012). Most changes impinge on capital investment decisions,

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which can invariably involve large sums of money over the long period (e.g.,Peterson & Fabozzi, 2002, Cooper et al.,

2002; Dayananda, Irons, Harrison, Herbohn & Rowland, 2002) and these decisions are critical in managing strategic

change and sustaining long term corporate performance (Emmanuel, Harris & Komakech, 2010). Capital investment

decision can be acquisitions, investing new facilities, new product development, employing new technology and

adoption of new business processes or some combination of these (Emmanuel et al., 2010). Capital budgeting

investment decisions are critical to survival and long term success for firms due to many factors and those factors are

commonly named as uncertainty. The global financial crisis is epitomized this truth. One of the most intractable issues

confronted by researchers is how to identify, capture, and evaluate uncertainties associated with long term projects

(Haka, 2006). Sources of uncertainty range from the mundane (cash flow estimation, number and sources of estimation

error, etc.) to the more esoteric (complementarities among investments, options presented by investment opportunities,

opportunity cost of investments, etc.) (Haka, 2006). Since capital investment decision deals with large sum of fund,

scrupulous attention has been given in making decision. ‗Capital budgeting is as the procedures, routines, methods and

techniques used to identify investment opportunities, to develop initial ideas into specific investment proposals, to

evaluate and select a project and to control the investment project to assess forecast accuracy‘(Segelod,1997). Albeit

there are number of capital budgeting methods assist in making decision, number of other uncertainty factors have

deleterious penetration into making capital budgeting decision.

Nowadays, complex methods are used for making capital budgeting decision rather purely depends on theories of

capital budgeting because of uncertainty and other contingency factors (Singh, Jain &Yadav, 2012; Zhang, Huang

&Tang, 2011; Kersyte, 2011; Bock & Truck, 2011; Byrne & Davis, 2005;Cooper et al, 2002; Arnold & Hatzopoulos,

2000; Mao, 1970; and Dickerson, 1963). After the advent of full-fledged globalization and in the era of cutthroat

competition (Verma, Gupta & Batra, 2009), advanced developments in technologies, other macro environmental factors

and demographic factors are intruding into capital budgeting practices (Verbeeten, 2006). In a world of geo -political,

social as well as economic uncertainty, strategic financial management is of process of change, in turn requiring a re-

examination of the fundamental assumption (e.g, efficient market hypothesis, Fama,1970) that cut across traditional

boundaries of the financial management (Hill, 2008). With limited credit and other sources of financing in today‘s

uncertain and challenging economic environment, also required to be scrupulously evaluated the profitability and

successfulness of proposed capital investments and allocate limited capital is more vital than ever (Kester & Robbins,

2011).

Over the last 20 years, there have been many changes and challenges in making financial decision due to the global

financial crisis, fluctuations in value of money, advanced technology, interest rate, exchange rate and inflation rates‘

risks and dramatic changes in economic and business environment both in national as well as in global markets. Thus,

there is need to re- examine and re- study for re-building capital budgeting practices since it has considerable impact on

investment decision making. The investment decision making is not a simple or straightforward approach, the risk is an

important element in making investment decision. There are number of risk techniques employed by companies for

evaluating investment projects. However, there is problem in setting up theoretical model and applying that model into

practice (e.g: Arnold & Hatzopoulos, 2000; Digkerson, 1963). Thus, the theory is not purely able to apply at all times.

Sometimes theories developed in the past do not applicable today. There is no doubt, over the last two decades

corporate practices regarding capital budgeting practices have not been static, diverged from the theories.

This study presents systematic review on capital budgeting practices literature published in the last two decades. The

systematic review of literature is referred to as 'principally justified by the manner in which the reviewer proceeds, stage

by stage, with full transparency and explicitness about what is (and what is not) done, typically using a protocol to

guide the process' (Young, Ashby, Boaz & Grayson, 2002, p.220). Through this review, updating information about the

capital budgeting techniques which being used by firms and to compare the current usage of various techniques,

methods with those found in previous studies. This study is thus accumulatively builds a robust knowledge in the area

of capital budgeting practices and identifying unearth gaps will become springboard for future research. Therefore, this

research guides the researchers to reflect on and assess where they are in an area of capital budgeting practices and

guide future research directions.

1.1 Objective of the study

Examining empirical research on capital budgeting practices to date has been very useful in explaining importance of

capital budgeting practices for the long time success of the business organization. Nowadays, complex methods are used

for making capital budgeting decision rather purely depends on theories of capital budgeting. Advanced developments

in technologies, other macro environmental factors and demographic factors are intruding into capital budgeting

practices and thus some of the theories become out of use in well developed countries (e.g: payback period). Thus, the

main aim of this research is to demonstrate unearth gaps in the existing capital budgeting practices literature and to

suggest the directions for the future research .It will further attempt to

Applied Economics and Finance Vol. 3, No. 2; 2016

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- Explain the capital budgeting theories and practices in different countries and demonstrate the disparities between theories and practices of capital budgeting

- Identify the factors that determine use of capital budgeting practices of a country or firm

1.2 Problem Statement

During the past twenty years (1993-2013), the theory of capital budgeting has been characterized by the many increased

applications on the basis of risk and uncertainty resulting from global economic, technological and advanced educational

changes e.g: inflation risk, interest rate and exchange rate risk. Capital budgeting is the backbone of the financial

management. Modern financial management theory generally assumes that the primary objective of a firm is to

maximize the wealth of its owners (Atrill, 2009). Uncertainty and risk are the major influence in making investment

decision and thus Mao (1970) says ‗a central aspect of any theory of capital budgeting is the concept of risk‘ (p.352). In

order to implement the objective of modern financial management theory, ‗financial executives need criteria for

choosing between alternative time patterns of project evaluations within his planning horizon' (Mao, 1970). There are

complexities in making investment decision and the theory could not always applicable in all situations. Problem

statement of this study is how far capital budgeting theory differentiates with practice and to demonstrate the nature

of the gaps in existing capital budgeting literature.

1.3 Research Questions

On the basis of background of research, the following research questions have been developed as the way to attain

research objectives.

 What are the capital budgeting theories and practices used by firms? Are there any disparities between

the capital budgeting theories and practices? If so how?

 What are the factors determines the use of capital budgeting practices? Are there different across

countries? If so how?

 What are the gaps in the existing capital budgeting literature?

2. Methodology

The main objective of this study is to find out gaps in extant capital budgeting literature during the past 20 years of

study. The methodology covers research philosophy, research approach, research strategy, methods of data collection

and data analysis. These entire methodological spheres used throughout the research have been below discussed in

details.

2.1 Research Philosophy

One of the dominant philosophical concepts is the ‗ontological assumption‘ that enquires about nature of reality, and

any study absence of this assumption would be treated as 'blinded' (Easterby-Smith, Thorpe & Lowe, 2002, p. 27). This

research assumes that capital budgeting practices are different across firms/ nations and the ways of looking at capital

budgeting practices are not same at all the time. It can be further articulated that even when there are number of capital

budgeting theories, we cannot expect similar application at all situations and thus it is subject to changes. Thus, the

ontological assumption is of constructionism. Constructionist ontology‘s view that world is being internally constructed

and both individually and collectively generate meaning where we are not sure about what is real! Consequently, people

guess reality of the world with the experience of external indicators.

Another important philosophical assumption is the epistemological assumption. It enquires about what should be taken

as acceptable knowledge in a particular field (Easterby-Smith et al., 2002). The traditional practices do not applicable in

the contemporary borderless global businesses and thus try to understand the factors determine the use of capital

budgeting practices. It guides how can we understand and determine capital budgeting practices in different context and

in different geographical location. The knowledge can be attainable by text analysis with subject methods. Thus, it

offers what is already known about capital budgeting practices and captures the gaps in extant literature by

systematically reviewing literature.

This research takes interpretive approach on epistemology for answering research questions. The reality is not

independent of individual thought and thus all the research findings are not similar with one another (Blaikie, 2007).

Thus, this multiple reality is called ‗subjectivism‘. Findings could vary in different context such as nature of

measurement tools, geographical location, company‘s size, organizational practices, types of sectors and form of

methodology used. Thus, this research is organized by collecting relevant literature review and interpreting concepts of

relationship between researchers and research. Inductive approach is thus suited by exploring thematic text analysis.

2.2 Research approach

The research strategy leads to design qualitative research approach. This research covered sufficient researches carried

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out during the past two decades in the area of capital budgeting. This research analyzed past literature by identifying

relevant themes and then thematic text analysis was employed. Thus, this research is ‗subjective‘ and adopts inductive

approach in order to answering research questions.

2.3 Research strategy

Research strategy tells about how research should be designed for answering a set of developed research questions and

consequently research aims are attained. As this research covers last twenty years of research papers carried out in the

area of capital budgeting from 1993 to 2013, this study adapts research strategy of longitudinal research design.

However, the collection of literature covers broad areas including different sectors, different locations/countries and

different size of firms. Thus, the systematic literature review sometimes takes comparative research design as well.

2.4 Data collection methods

Web of science search and iCat search were used to locate research papers published during the last twenty years. Web

of science is a mass search engine linking with mass database covering more than 10000 journals and 110 000

conference proceedings. However, all most all the databases (online the full text of electronic resources) have been

covered by iCat search which is subscribed and launched by Kingston University, London. Kingston University

library‘s access service was exploited for collecting all the research papers. Search parameters includes capital

budgeting, capital budgeting decision, capital budgeting theory, capital budgeting practices, capital budgeting methods,

capital budgeting models, capital budgeting tools, capital budgeting techniques, capital budgeting process and

investment decision.

Initially, there are 363 research papers identified during the last 20 years. Of them, 201 research papers were screened

and considered for this research to be reviewed based on the following criteria.

- An empirical study (i.e., sampling process, measurement , analysis): 363 papers were identified - Published in English language: Of 363, 264 were published in English. - Should be published in peer reviewed journal : Of 264, 239 were published in a peer reviewed journals - Full text research papers: Of 239, 201 papers were full text journal

These papers were collected from following databases: OneFile (GALE), SciVerse ScienceDirect (Elsevier), Informa -

Taylor & Francis (CrossRef), Wiley (CrossRef), Business (JSTOR), Arts & Sciences (JSTOR), MEDLINE (NLM),

SpringerLink, Wiley Online Library , Inderscience Journals , ERIC (U.S. Dept. of Education), Sage Publications

(CrossRef), INFORMS Journals, Health Reference Center Academic (Gale), University of Chicago Press Journals,

Emerald Management eJournals, Directory of Open Access Journals (DOAJ),IngentaConnect, IEEE (CrossRef). All

these papers were spread over across many journals including Journal of Banking and Finance, The Journal of Finance,

Journal of Accounting and Economics, Management Decision, Journal of Cleaner Production, Journal of Financial

Economics, Management Science, European Journal of Operational Research, Accounting Review, Journal of

Economic Behavior and Organization, Long Range Planning, Energy Policy, Accounting, Organizations and Society,

Computers and Mathematics with Applications.

2.5 Data analysis

As discussed, at the outset, Miles and Huberman‘s (1984) proposed strategy was carried out that involves collection,

reduction, displays and conclusions. Based on the set criteria, 363 research papers were reduced to 201 and they

analyzed using a coding procedure. Initially, collected research papers were grouped into themes or topics. Theme

represents the focused area of research and it is selective coding on grounded theory (Corbin & Strauss, 1990). Themes

were in terms of current theory and practices of capital budgeting, factors influencing on capital budgeting practices/

determinants of capital budgeting practices, capital budgeting methods/ models, supplementary tools for the capital

budgeting methods, influences of capital budgeting practices on investment decisions, component of capital budgeting

process, capital budgeting stages, and global capital budgeting practices.

A thematic analysis was employed to capture key themes and concepts in chosen research papers. In doing so, open

coding, as suggested by Strauss and Corbin (1998), was adopted. The analysis was focused on the concepts related to

capital budgeting practices and theories, research design, research sampling techniques, research approach, year of

publication, nature of industry and so on. The results of this analysis were presented below.

3. Results

3.1 Multi-disciplinary concepts of capital budgeting

During the past twenty years, a total of 202 research papers appeared in peer reviewed indexed journals were identified

across many academic journals. Majority of the papers appeared in Engineering Economist (N= 32) yielding 15.92%

followed by Managerial Finance (27), Public Budgeting & Finance (16), Financial Management(9), Journal of Banking

and Finance (8), Journal of Business Finance & Accounting (6), Accounting Education(5), Management Accounting

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Research(5), The Journal of Finance(5), Journal of Corporate Accounting & Finance (4), Management Decision (4) and

The Review of Financial Studies. All of these journals represented 62.20 % of research papers in capital budgeting in

the last two decades. The reminder of the research papers appeared in many journals. Capital budgeting is thus

multi-disciplinary aspects and applied across many discipline. The table 1 below summarizes entire list of journals

contained capital budgeting research papers.

Table 1. Name of the journals: Capital budgeting research papers appeared during the past twenty years

Name of the Journal Number of

paper

published

Percentage

Engineering Economist 32 15.92%

Managerial Finance 27 13.43%

Public Budgeting & Finance 16 7.96%

Financial Management 9 4.48%

Journal of Banking and Finance 8 3.98%

Journal of Business Finance & Accounting 6 2.99%

Accounting Education 5 2.49%

Management Accounting Research 5 2.49%

The Journal of Finance 5 2.49%

Journal of Corporate Accounting & Finance 4 1.99%

Management Decision 4 1.99%

The Review of Financial Studies 4 1.99%

Three papers in each journal: Healthcare Financial

Management, Information Sciences, International Journal of

Energy Research, International Journal of Production Economics,

Journal of Financial Economics, Management Science,

Operations Research, The Journal of Business, Theoretical and

Applied Economics.

3 1.49%

Two papers in each journal: Accounting & Finance, Accounting

and Business Research, Accounting, Organizations and Society,

Computers & Industrial Engineering, Computers and

Mathematics with Applications, Contemporary Accounting

Research, European Financial Management, European Journal of

Operational Research, Health care strategic management,

Industrial Management & Data Systems, International Journal of

Business and Management, Journal of Accounting and

Economics, Journal of Computational and Applied Mathematics,

Journal of Information Technology, Journal of Marketing

Management, Journal of Small Business Management, Journal of

the International Academy for Case Studies, Journal of the

Operational Research Society, Long Range Planning, Managerial

and Decision Economics, The Bond Buyer, The Financial

Review.

2 1.00%

One paper in each journal: Academy of Marketing Studies

Journal, Accounting Review, Agricultural Finance Review.

1 0.50%

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Applied Financial Economics, Australasian Radiology, Australian

Journal of Management, BuR : Business Research, Business

Forum, Wntr-Spring, Business Process Management Journal,

Canadian Journal of Anesthesia/Journal canadien d'anesthésie,

Computational Management Science, Computers and Chemical

Engineering, Cornell Hotel and Restaurant Administration

Quarterly, Energy Policy, European Management Journal, Expert

Systems With Applications, Forest Products Journal, Fuzzy Sets

and Systems, Healthcare financial management. IEEE

Transactions on Engineering Management, Industrial

Management, International Journal of Commerce and

Management, International Journal of Information Technology &

Decision Making, International Journal of Project Management,

International Journal of Quality & Reliability Management,

International Transactions in Operational Research, Journal of

Accounting Research , Journal of Cleaner Production, Journal of

Economic Behavior and Organization, Journal of Empirical

Finance, Journal of Hospitality & Tourism Research, Journal of

International Financial Management & Accounting, Journal of

International Money and Finance, Journal of Management

Accounting Research, Journal of Managerial Issues, Journal of

Property Investment & Finance, Journal of Public Health

Dentistry, Journal of Retail Banking, Journal of Risk and

Insurance, Journal of Teaching in International Business, journal

of the Healthcare Financial Management, Knowledge-Based

Systems, Management Accounting Quarterly, Mid-Atlantic

Journal of Business, Naval Research Logistics (NRL), New

Directions for Higher Education, Operations-Research-Spektrum,

Quarterly Review of Economics and Finance, Real Estate

Economics, Review of Agricultural Economics, Review of

Business, Review of Finance and Banking, Review of

Quantitative Finance and Accounting, Scandinavian Journal of

Management, South East European Journal of Economics and

Business, Strategic Finance, The Accounting Review, The

European Journal of Finance, The Financier, Spring-Winter, The

McKinsey Quarterly, Tsinghua Science & Technology, UTMS

Journal of Economics, Vision: The Journal of Business

Perspective, Journal of advances in management research.

Percentages calculated in terms of number of papers appeared in each journal (N = 202).

3.2 Major themes identified in Capital budgeting research

A total of 201 research papers in capital budgeting have been meticulously reviewed and consequently following major

themes have been identified: capital budgeting theory and practices, capital budgeting theory and practices in developed

countries, capital budgeting theory and practices in developing countries and factor affecting capital budgeting decision.

Findings discusses under identified themes.

3.3 Capital budgeting theory and practices

Capital budgeting decisions are crucial and complex and have attracted many research scholars in this field. According

to Dayananda et al. (2002), capital budgeting is the process of deciding investment projects which create in

maximization of shareholder value. Capital budgeting is mostly dealt with sizable investments in long term assets.

Assets can be either tangible such as building, plant, or equipment or intangible assets such as patents, new technology

or trade mark (Brealey & Myers, 2003). Capital budgeting is not a short term aspects, generally prepared a year in

advance and extendable to five, ten or even fifteen years in future (Brickley, 2006). And thus, Peterson and Fabozzi

(2002) define capital budgeting is the process of analyzing and selecting investment opportunities in long term assets

where its benefits last for more than one year.

Capital budgeting is a fundamental and used everywhere as a tool for planning, control, and allocation of scare

resources among competing demands. Capital budgeting is a vital part in financial planning and decision making since

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capital budgeting tools leads better decision making and be able to justify selection of specific capital investments

among competing alternatives (Sekwat,1999).Decision to choose the best investment project among competing projects

is of critical and being taken by top management (Bowman & Hurry, 1993; McGrath, Ferrier & Mendelow, 2004) and

considerable attention is thus to be given to investigating the methods used in evaluating and selecting investment

projects (Sangster, 1993; Segelod, 1998).

The most prevalent capital budgeting techniques in the public finance literature include payback period (PB),

accounting rate of return (ARR), net present value (NPV), internal rate of return (IRR), benefit-cost ratio (BCR), and

profitability index (PI) (e.g., Sekwat,1999;Cooper et al.,2002). Among these methods, four methods .viz., NPV, IRR,

PB and ARR, have been identified as a predominant method and used in many studies (e.g., Pike,1996; Kester, Chang,

Echanis, Haikal, Isa, Skully,Tsui & Wang, 1999; Hermes, Smid, & Yao , 2007).

The PB model determines the length of time required to recover exactly the invested cash outlay. On the other hand, the

ARR is calculated as the ratio of the investment‘s average after tax income to its average book value (Cooper et al.,

2002). The PB period has been criticized for failing to make accurate assessments of project value as it does not

consider use of cash flows, time value of money, risk in a systematic manner and further it does not identify investment

projects that will maximize profits, therefore PB does not have theoretical justification (Pike, 1988; Lefley,1996).

Research scholars and practitioners criticized the ARR due to the ignorance of the time value of money (e.g., Cooper et

al., 2002; Ross, Waterfield, Jordan & Roberts, 2005). And PB methods failed to consider return from the capital

investment after the initial outlay recovered, yet it is also oft- used methods (e.g., Graham & Harvey, 2001; Brounen et

al., 2004; Bennouna, Meredith and Marchant, 2010). Researchers argued that the reasons behind widespread use of PB

method are of its easiness and of providing information about recovery of initial investment.

Thus, in the next generation, the NPV model came into practice where it measures the difference between present value

of the money in and present value of the money out (Cooper et al., 2002). If the NPV is positive, the capital investment

is accepted and vice versa. Alternatively, the IRR determines the rate at which capital investment can be acceptable and

thus equates the cost of the capital investment to the present value of that project (Cooper et al., 2002). In finance, the

methods of assessing capital budgeting using the concepts of the time value of money is called discounted cash

flow (DCF) analysis. The NPV and IRR methods are called discounted cash flow (DCF) methods. The PB and ARR

methods are considered to be non-DCF methods. ‗Capital budgeting theory assumes that projects are evaluated based on

economic merit. Building upon certain economic assumptions, including the time value of money, risk aversion, and an

assumed goal of value maximization, sophisticated investment appraisal techniques such as NPV and IRR, have been

advocated in the literature‘ (Slagmulder et al., 1995,p.123).Notwithstanding, several researchers criticized that requisite

necessary information for NPV and IRR is commonly not known with certainty owing to longer periods, uncertainty

in future, higher degree of risk, ignore the size of the investment and absence of logical comparison on time value of

money (e.g., Sekwat,1999;Cooper et al.,2002; Hermes et al., 2007).Thus, in order to overcome both the time value of

money and the size of the investment, the PI model has been emerged. It is the ratio of the capital investment to its

outlay and the decision being made in terms of the highest PI (Cooper et al., 2002). If this method used carelessly with

constrained investment resources, it generates bad results (Brealey & Myers, 2003).

However, Graham and Harvey (2001) reported that twelve capital budgeting methods were in practice: NPV, IRR,

Annuity, Earning multiple (P/E), Adjusted present value (APV), PB, Discounted Payback, PI, ARR, Sensitivity analysis,

Value at risk and real options. However, all of them are not in usable at all situations in capital budgeting practices. For

example, IRR should not be the best method if investments are mutually exclusive or have multiple rates of return,

however, IRR is oft-exploited methods in practice (Graham & Harvey, 2001; Brounen et al., 2004; Bennouna et al.,

2010).

Of these methods, discounted payback considers time value of money but it still ignores cash flows after initial outlay

recovered. Value-at-risk (VAR) is to measure 'the worst expected loss over a given horizon under normal market

conditions at a given confidence level' (Jorion, 2006; p.12), is a relatively new method. The APV additionally covers the

value of financial side-effects of an investment to NPV, and treated as having no drawbacks principally (Ross et al.,

2005).

The greatest problems of the traditional present value models are that its complete reliance on quantifiable cash flows.

However, in a contemporary high tech world, many new projects entail complete redesign of the manufacturing

environment and computerized design is of paramount important to be innovative, higher qualities and speedier

response (Cooper et al., 2002). And thus, the theory of capital budgeting is diverged from its practices.

The complex nature of the capital investment in today‘s world incubates many new models into practices including

multi-attribute decision model, and analytical hierarchy process that are more subjective (Cooper et al., 2002). Modern

theoretical developments in finance views that DCF methods are not the best methods to select capital investment

projects: they have severe drawbacks in the analysis of investment projects if the information about future investment

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decision is not available (Brennan & Schwartz, 1992; Trigeorgis, 1993; Dixit & Pindyck, 1994). In such a situation,

Real Options Reasoning (ROR) and Game Theory (GT) serves as better analytical tools to evaluate such investment

projects (Smit & Ankum, 1993). GT stresses that firm is having an incentive to invest early in the case of fear of

pre-emption (Smit, 2003)

Real option theory: Real option is closely related to corporate capital investment decision-making and has been

introduced as an alternative approach for investment appraisal under uncertainty. The starting point for real options

research was the criticism of traditional strategic investment decision-making and capital budgeting methods. In general,

a real option represents or reflects the option or options that a company has when it comes to deciding whether to invest

in a project, delay, put it on hold, expand or reduce an investment, or any other flexibility that it may have (Rigopoulos,

2014). ROT involves the use of investment evaluation tools and processes that properly account for both uncertainty and

the company‘s ability to react to new information (Verbeeten, 2006). ROT has operating flexibility (which enables the

management to make or revise decisions at a future time, such as expansion or abandonment of the project) and the

strategic option value (resulting from interdependence with future and follow-up investments, such as implementation in

phases and the postponement of investments) (Verbeeten, 2006). Many researchers have argued that the use of real

options analysis has an advantage over NPV, since NPV is not able to capture the value of managerial flexibility (e.g.,

Ingersoll & Ross, 1992; Trigeorgis, 1993; Dixit & Pindyck, 1994). For example, the management could delay, expand,

abandon, temporarily close or alter the operation during the project‘ life. Ross et al. (2005) argued that most capital

investment projects have options (i.e., the option to expand, the option to modify, the option to abandon), which have

value per se. Although this method has not been applied on a large scale in practice (Hermes et al., 2007), it is mostly

applicable in specific industries or situations. DCF techniques are used concurrently with real options in order to

determine the true NPV (Amram & Howe, 2002). Many research scholars have found that only a few firms have

employed real options (Graham & Harvey, 2001; Ryan & Ryan, 2002; Brounen et al., 2004; Block, 2007; Truong,

Partington & Peat,2008; Verma et al., 2009; Bennouna et al., 2010; Shinoda,2010, Singh et al.,2012; Andres, Fuente &

Martin,2015).

It is obvious that widespread use of sophisticated capital budgeting during the last two decades. Many earliest studies

investigated about capital budgeting decision rule, in contrast, recent researches attempted to focus on the use of

sophisticated capital budgeting practices (e.g., Miller & Waller, 2003). Application of sophisticated capital budgeting is

more complex, and required the firms to be able to expend cost, time and effort (Busby & Pitts, 1997; Miller & Waller,

2003). Thus, it is important to think about the appropriate level use of sophisticated capital budgeting practices to the net

benefits against costs. Anyhow, theory, in contrast, suggests that if uncertainty exists, use of sophisticated capital

budgeting practices is valuable and the costs would be offset by the gains from successful investments (Verbeeten, 2006).

If uncertainty exists, additional information needed to solve the problem of investment dilemma (Miller & Waller, 2003).

It was identified that Canadian firms seem to be increasingly using sophisticated methods when dealing with risk (for

example, sensitivity analysis, decision-tree analysis, Monte Carlo simulation, ROR, GT) (Bennouna et al., 2010).

Nowadays, there are number of other methods including the project-dependent (risk-adjusted) cost of capital (PDCC), the

weighted average cost of capital (WACC), the cost of debt (CD) used in capital budgeting practices. Among them PDCC

and WACC are said to be sophisticated method and CD is the least sophisticated method (Hermes et al., 2007).

3.4 Capital budgeting tools for incorporating risk

Overall, uncertainty affects future cash flows and causes estimation difficulties. Therefore, various risk analysis and

management science techniques have been developed to supplement the traditional present value based decision models.

Scholarship on the practice of capital budgeting in many countries has found that firms are increasingly employing

more sophisticated capital budgeting techniques in order to make investment decisions over several years (Klammer,

1973; Klammer & Walker,1984; Pike,1988; Jog & Srivastava,1995; Gilbert & Reichart,1995; Farragher, Kleiman &

Sahu,1999; Arnold & Hatzopoulos, 2000; Brounen et al.,2004; Truong et al., 2008; Baker, Dutta & Saadi,2011). In the

contemporary world, there are a number of sophisticated capital budgeting methods including the oft-cited: Monte

Carlo Simulations, Game theory decision rules , Real option pricing, Using certainty equivalents, Decision trees, CAPM

analysis / ß analysis, Adjusting expected values, Sensitivity analysis/break-even analysis, Scenario analysis, Adaptation

of required return/discount rate, IRR, NPV, uncertainty absorption in cash flows, and PB (e.g., Arnold & Hatzopoulos,

2000; Hall, 2000; Graham & Harvey, 2001; Ryan & Ryan, 2002; Murto & Keppo, 2002; Cooper et al., 2002; Smit, 2003;

Sandahl & Sjogren, 2003; Brounen et al., 2004; Lazaridis, 2004; Lord, Shanahan & Bogd, 2004; du Toit & Pie naar,

2005;Verbeeten, 2006; Elumilade, Asaolu & Ologunde, 2006; Hermes et al., 2007; Leon et al., 2008; Correia &

Cramer, 2008; Verma et al., 2009; Bennouna et al., 2010; Shinoda, 2010; Hall & Millard, 2010; Dragota et al, 2010;

Poudel et al., 2009; Kester & Robbins, 2011; Maroyi & Poll, 2012; Singh et al., 2012; Andres et al., 2015). Thus, the

complex models of capital budgeting practices are dependent on not only the use of DCF techniques, but also proper

cash flows, discount rates and the risk analysis (Brigham & Ehrhardt, 2002).

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3.5Classification of Capital budgeting Practices

Capital budgeting practices help managers to select n out of N investment projects with the highest profits and an

acceptable ‗risk of ruin‘ (Verbeeten, 2006, p.108). By and large, all capital budgeting practices can be subsumed into the

categories of sophisticated, advanced and naive (e.g., Haka, 1987; Haka, Gordon & Pinches, 1985; Verbeeten, 2006;

Wolffsen, 2012). Naive practices includes PB, the adaptation of required payback and ARR, and the advanced /NPV

based, including Sensitivity analysis/break-even analysis, scenario analysis, the adaptation of required return/discount

rate, IRR, NPV, uncertainty absorption in cash flows, MIRR and PI. Farragher et al. (2001) suggested that a degree of

sophistication is represented by the use of DCF techniques and incorporating risk into the analysis. Sophisticated capital

budgeting methods generally include Monte Carlo simulations, GT, RO, using certainty equivalents, decision trees,

CAPM analysis / ß analysis, and adjusting expected values (Verbeeten, 2006; Wolffsen, 2012).

3.6 Capital budgeting theory and practices in developed countries

This section clearly discusses the capital budgeting theory and practices especially in developed countries. As

aforementioned, the capital budgeting practices are the investment decision taken for increasing shareholders value

(Dayananda et al., 2002).

Many studies have been conducted about capital budgeting practices in U.S. and Europe (e.g., Pike, 1996; Sangster,

1993; Block, 2007; Herme et al., 2007). Chadwell-Hatfield et al.(1997) conducted a survey among 118 manufacturing

firms in the U.S. Results showed that NPV (84%) and IRR (70%) were preferred primary methods. However, it was

clearly observed that two thirds of firms relied on shorter PB periods rather IRR or NPV. A seminal study carried out by

Graham and Harvey (2001) about ‗the theory and practice of corporate finance: evidence from the field‘ and the sample

consisted of 392 CFOs in the USA. In larger firms with high debt ratio, CFOs with MBA were more likely to use DCF

(75% NPV and IRR) than their counterparts. Larger firms applied risk-adjusted discount rate whereas small firms opted

for Monte Carlo simulation for adjusting risk. In addition, their findings further argued that PB method has not used

as a primary tool, however, it kept as a vital secondary tool. Very similar results were reported in Ryan and Ryan‘s

(2002) study where sample consisted of Fortune 1000 companies. Results were found that NPV was most popular

technique, followed by IRR. Most of the firms used sensitivity analysis, scenario analysis, inflation adjusted cash flows,

economic value added, and incremental IRR along with NPV and IRR. Block (1997) studied about capital budgeting

techniques across small business firms operating in the United States. The most popular method was the PB (42.7%),

followed by ARR (22.4%). Notwithstanding, researchers connotes that small business owners seemed to be increasingly

using DCF as the primary method for evaluating.

Cooper et al. (2002) studied capital budgeting practices in fortune 500 companies in America. Sample consisted of 102

chief financial officers reported that commonly used primary capital budgeting model is the IRR and the second is the

payback. Ken and Cherukuri (1991) found that IRR was mostly preferred method in larger companies operating in the

U.S. NPV was the next preferred method. The widely used discount rate was the WACC (78%) and the risk was

commonly measured by sensitivity analysis (80%).Almost similar results were reported in the survey of Fortune 100

firms by Bierman in 1993.

Arnold and Hatzopoulos (2000) conducted a study on "The gap between theory and practice in Capital Budgeting:

Evidence from the UK for 300 UK companies (comprising 100 large, 100 medium and small 100). Results of study

indicate that UK companies have increasingly adopted the analysis of financial textbooks prescribed. Stage has been

reached in which only a small minority do not make use of discounted cash flows, formal risk analysis, adjustment

corresponding inflation and post-audit in their study. Study reported however, managers still using simple rules of

thumb techniques in UK

Jog and Srivastava (1995) conducted a survey of capital budgeting practices in Corporate Canada and the results

showed that the most preferred method was the PB. Similar results were found in the UK in Pike‘s (1996) study. Further

results indicated that decreased use of ARR in Canada and the United Kingdom, respectively. It was identified that

Canadian firms seem to be increasingly using sophisticated methods when dealing with risk (for example, sensitivity

analysis, decision-tree analysis, Monte Carlo simulation, ROR, GT) (Bennouna et al., 2010).

Drury, Braund and Tayles (1993) surveyed 300 manufacturing companies in the UK about their capital budgeting

practices. Results showed that PB (86%) and IRR (80%) were mostly preferred methods across the sample. The widely

used risk analysis was the sensitivity analysis. In a seminal study of Brounen et al. (2004), four European countries

viz., U.K., France, Germany and the Netherlands consisting of 313 companies during 2002 and 2003 were examined.

Their result showed that 47% and 67% of the UK companies were used NPV and PB respectively as a primary tool for

evaluating capital budgeting decision whereas companies in Netherlands were used 70% of NPV and 65% of PB

methods. However, companies in France and Germany reported lower usages of both methods (42% for NPV, 50 % for

PB and 44% for NPV, 51 % for PB respectively). Previous studies have mainly conducted in the U.S. and the UK and

Applied Economics and Finance Vol. 3, No. 2; 2016

24

limited number of studies are also available for the Netherlands (e.g., Herst, Poirters & Spekreijse, 1997; Brounen et al.,

2004).

Many researches recognized that DCF is the dominant in capital budgeting evaluation methods in the UK (e.g., Arnold

& Hatzopoulos, 2000), the USA (e.g., Ryan & Ryan, 2002) and in Canada (e.g., Payne et al., 1999). However, most of

the US firms use DCF techniques in comparison with firms in European countries (e.g., Brounen et al., 2004). There is

still some reluctance in this field due to the technical aspects of DCF (e.g., Cary, 2008; Magni, 2009). In 1993, Bierman

and Smidt opined that the DCF methods are the pre-eminent investment decision tool and thus, it is imperative to

manager to learn about its uses. Anyhow, NPV, IRR and PB are the most popular methods among North American and

Western European companies (Graham & Harvey, 2001; Brounen et al., 2004).

Sekwat (1999) studied capital budgeting practices among 321 Tennessee municipal governments. His results showed

that most of the municipal government‘s organizations are using benefit cost ratio (62.5 %) and payback methods

(61.5%), and financial officers were in reluctant using IRR, ARR and even NPV methods. Holmen (2005) conducted a

survey of capital budgeting techniques, used for FDI‘s by Swedish firms and found that larger firms were preferred to

use NPV and IRR methods. However, the most preferred method was the PB (79%). In a survey of capital budgeting

practices of Australian listed companies, Truong et al., 2008 found that NPV, IRR and PB were the most popular capital

budgeting evaluation methods. Researchers were also identified the use of real option across the sample but not yet part

of the mainstream.

In 2009, Kester and Robbins surveyed about capital budgeting techniques used by Irish listed companies. Results

revealed that they use DCF methods and reported that most prevalent method was NPV, followed by PB, and IRR.

Scenario analysis and sensitivity analyses were found to be most important tools for incorporating risk. WACC was the

most important widespread method employed for calculating discount rate. On the other hand, Lazaridis (2004) studied

capital budgeting practices in Cyprus. The PB was found as the most preferred method and not NPV.

Shinoda (2010) carried out a survey of capital budgeting in Japan. Questionnaire has been administered to collect data

from a sample of 225 companies listed on Tokyo Stock Exchange. Results showed that firms were using combination of

PB and NPV for evaluating capital investment projects.

In summary, many studies have found that increasing use of sophisticated capital budgeting techniques among many

developed countries: US, UK, European and Australian companies (Freeman & Hobbes, 1991;Shao & Shao, 1996;

Pike, 1996; Herst, Poirters & Spekreijse, 1997; Brounen et al., 2004 ; Truong et al., 2008). However, US companies

seem to be using more DCF methods as compared to European countries.

3.7 Capital budgeting theory and practices in developing countries

There is dearth of studies carried out on capital budgeting practices in developing countries during the last two decades.

In comparison with developed countries, the results of the most studies show a different picture. In most of the

developing countries, PB method was the dominant methods in evaluating capital investment. Kester et al.(1999)

surveyed a total of 226 companies across six countries: Australia, Hong Kong, Indonesia, Malaysia, Philippines and

Singapore. Results showed that PB is still important method and the DCF methods have become increasingly important.

In five Asian countries, 95% of firms used PB method and 88% of them use NPV in evaluating projects. However, both

methods were treated as equally important. Kester et al. (1999) noted that sophistication of capital budgeting techniques

within the developing countries in Asia has been increased very rapidly during the last decade.

Babu and Sharma (1996) studied Indian industries‘ capital budgeting practices and the findings showed that 90% of the

companies were using capital budgeting methods. Of them 75% of companies reported that they were adopting DCF

methods in evaluating capital budgeting, among them IRR was most popular. Sensitivity analysis was found to be

popular in assessing risk. In 1998, Jain and Kumar studied about comparative capital budgeting practices: the Indian

context and sampled 96 nongovernment companies where listed in Bombay Stock Exchange and five companies of

South East Asia. They observed that most preferred capital budgeting techniques was the PB (80% companies),

followed by NPV and IRR. Sensitivity analysis was the preferred risk assessment method.

Cherukuri (1996) surveyed about capital budgeting practices: a comparative study of India and select South East Asian

countries,‖ with those of Hong Kong, Malaysia and Singapore and a sample consisted of top 300 non-government

companies. This study found that of DCF methods, 51% of companies used IRR, followed by NPV (30%). Of non DCF

methods,PB (38%) is the dominant method and the next widely used method was ARR (19%). The non DCF methods

were used as supplement to DCF methods. WACC is the widely used discount rate and Sensitivity analysis was mainly

used for risk assessment. A recent survey of capital budgeting Practices in corporate India, conducted by Verma et

al.(2009), took a sample of 30 manufacturing companies in India. The results confirmed findings of Cherukuri

(1996).This study showed that most preferred method is IRR (56.7%), followed by NPV (50%) and PB (36.7%).WACC

(43.3%) is the widely used discount rate and Sensitivity analysis (36.7%) was mainly used for risk assessment.

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Researchers further observed that increasing adoption of DCF rather traditional use of non-discounted techniques. In

2012, Singh et al. studied on capital budgeting decision sampling from 31 listed companies in India. Albeit capital

budgeting decision continued in India, all sampled firms reported that they are using DCF techniques in combining with

non-DCF techniques. Of discounted cash flow techniques, more than three quarters of the sampled companies use IRR

which more preferred than NPV that used by half of the sampled companies. Further it has been reported that half of

the companies use real option techniques in selecting their capital investment projects. Long term capital is of financing

source to finance fixed assets (net) and working capital (net) in India. Most of the variables are country specific;

researchers call for further detailed research considering sectorial analysis of the constituent sectors of the sample

companies would be shed new light on this area.

Hermes et al. (2007) carried out a comparative study of the Dutch and Chinese firms about capital budgeting practices.

66.7% of the Dutch CFOs stated that they used WACC and only 9.5 % of them used PDCC. Small firms use CD most

often (22.7%) in comparison with larger firms (5.0%). In the Dutch firms, 89% of CFOs reported that they used NPV

methods however, 2% of CFOs stated that they used the ARR which is the least popular method. In contrast, 53.3% of

Chinese firms indicated that they use WACC, and just 15.7% of CFOs of Chinese firms use PDCC. However, 28.9% of

CFOs reported that they use CD which is higher than that of the Dutch counterparts. Chinese CFOs stated that they

more likely to use NPV and PB methods (89% and 84% respectively) in evaluating capital budgeting projects. Thus, on

average, Dutch CFOs use more sophisticated capital budgeting techniques than Chinese CFOs do.

In 2008, Leon et al. conducted a survey of capital budgeting practices of listed companies in Indonesia. DCF was

mainly adopted methods in those companies as primary evaluation tool for capital investment projects. The most

prevalent risk assessment tools were scenario and sensitivity analysis. Results supported that CAPM was not so popular

Recently, a survey of capital budgeting practices have been conducted by Khamees, Al-Fayoumi, and Al-Thuneibat

(2010) in Jordan. Results reported that both DCF and non DCF method were still popular in evaluating capital

budgeting investment. Surprisingly, the most popular method was PI, followed by PB.

Most recently, Maroyi and Poll (2012) conducted a survey of capital budgeting practices in listed mining companies in

South Africa. Results showed that NPV, IRR and PB were the most prevalent methods in evaluating larger investment

projects. Results further indicated that PB was found to be continual use of method. Following table summarizes the

key findings on capital budgeting literature

Table 1. Key findings on capital budgeting studies during last two decades (from 1993 to 2013)

Author/s Population Most popular capital

budgeting method

Methods for evaluating

risk in Capital Budgeting

Drury, Braund & Tayles

(1993)

300 UK

Manufacturing

companies

PBP and IRR Sensitivity analysis.

Babu & Sharma (1995) 73 Indian

companies

DCF Methods Sensitivity analysis and

adjustment of discount

rate methods

Jog & Srivastava

(1995)

582 Canadian

companies

IRR and PBP Sensitivity analysis

Pike (1996) Large UK

companies

PBP

Kester & Chang (1996) 54 companies IRR and PBP Scenario and sensitivity

analysis

Farragher, Kleiman &

Sahu (1999)

379 US

companies in the

Standard & Poor‘s

industrial index

DCF Methods : NPV Capital Assets Pricing

Model

Sekwat (1999) 166 Finance

Officers of

Municipal

Governments

Cost-Benefit Ratio and

PBP

Applied Economics and Finance Vol. 3, No. 2; 2016

26

(Tennessee)

Kester , Chang,

Echanis, Haikal, . Isa,

Skully, Tsui, & , Wang

(1999)

226 companies in

Australia, Hong

Kong, Indonesia,

Malaysia, The

Philippines and

Singapore in 1996-

1997

Equal importance to

discounted and

non-discounted cash flow

techniques in evaluating

projects

Scenario analysis and

sensitivity analysis

Arnold & Hatzopoulos

(2000)

300 UK Companies DCF is widely using by

the selected UK firms.

Hall (2000) 65 Respondents

(South Africa)

IRR

Graham & Harvey

(2001)

392 Chief

CFOs of

companies in the

U.S.

NPV and IRR Large firms- risk adjusted

discount rate Small firms-

Monte Carlo Simulation

Ryan & Ryan (2002) 205US Companies NPV and IRR Sensitivity analysis,

Scenario analysis,

inflation adjusted cash

flows, economic value

added, and incremental

IRR

Sandahl & Sjogren

(2003)

129 Swedish

Corporations

PBP Annuity

Lord, Shanahan & Boyd

(2004)

29 Local authorities

of New Zealand

Local Government

Cost Benefit Ratio

Brounen, deJong &

Koedijk (2004)

Four European

countries viz.,

U.K., France,

Germany and the

Netherlands

consisting of 313

companies during

2002 and 2003

Primary tools were in UK

– NPV and PBP, in

Netherland – NPV and

PBP , France and

Germany reported lower

usages of both methods

(42% for NPV, 50 % for

PB and 44% for NPV,

51 % for PB

respectively).

Lazaridis (2004) Small Medium

Sized Companies

(Cyprus)

PBP Statistical Risk Analysis,

Scenario Analysis

Elumilade, Asaolu &

Ologunde (2006)

94 firms from

Nigerian stock

exchange (Nigeria)

PBP, ARR , and NPV Linear programming

Lam, Wang & Lam

(2007)

157 Hong Kong

Building

Contractors

PBP and Average

Accounting Rate of

Return

Shortening Payback

Period, Raising Required

Rate of Return

Dedi & Orsag (2007) 200 firms

selected from 400

of the best Croatian

firms & 34 banks

IRR, PBP (cost of capital

is calculated by WACC)

Risk-adjusted discount

rate, Certainty equivalents

for cash flows

Applied Economics and Finance Vol. 3, No. 2; 2016

27

from a ranking of

Croatian

banks

Truong, Partington &

Peat (2008)

87 Australian

companies

NPV, IRR and PBP Real options techniques

have gained a foothold in

capital budgeting but are

not yet part of the

mainstream. Capital

Assets Pricing Model is

found to be the most

popular method used in

the estimation of the cost

of equity capital

Leon, Isa & Kester

(2008)

229 Listed

Companies

(Indonesia)

DCF Techniques Scenario and Sensitivity

Analysis

Zubairi (2008) 35 firms listed on

KSE (Pakistan)

Bigger size companies

give greater preference to

IRR, while smaller firms

rely more on NPV.

Also smaller firms are

keener in estimating the

PBP as compared to larger

companies.

Verma, Gupta & Batra

(2009)

100 manufacturing

companies (India)

NPV and IRR Weighted Average Cost of

Capital (WACC) was to

calculate the Cost of

Capital. Sensitivity‘

analysis

Hall & Millard (2010) South African

industrial

companies listed

on the JSE

Securities

Exchange for at

Least ten years.

IRR

Dragota. Tatu, ,Pele,

Vintila, & Semenescu

(2010)

Professors in the

economic field,

having

competences in

Corporate Finance

and teaching in

Romania.

NPV, IRR or PI, Discount

Rate used for the

investment projects

analysis is the weighted

average cost of capital.

Sensitivity Analysis ,

Monte Carlo Method and

the Scenarios Technique

Shinoda (2010) 225 firms listed on

the Tokyo Stock

Exchange

PBP and NPV

Poudel, Sugimoto,

Yamamoto, Nishiwaki ,

& Kano (2010)

50 Farms (Nepal) Benefit-Cost ratio (B/C),

NPV, IRR, and PBP

Sensitivity Analysis

Bennouna,Meredith &

Marchant (2010)

88 Large Firms Trends towards

sophisticated techniques

(DCF) have continued. Of

those which did, the

The majority of Canadian

firms use risk analysis

tools mainly sensitivity

analysis followed by

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28

Source: Survey data

3.7 Factor affecting capital budgeting

In practice, there are numerous factors that heavily influence on capital budgeting decision. Behavioral finance become

increasingly important and intrudes into capital budgeting theory, and the knowledge on behavioral finance derived

from sociology and psychology. The behavioral finance states that capital investment decision is not solely dependent

on quantitative data, but the decision is also strongly influenced by qualitative data including institution and personal

values, tolerance to risk, situational context and so on. More recently, Ben-David, Graham, and Harvey‘s (2008) study

of CFOs found that overconfidence was a key driver of investment, however optimism found to be more marginal effect

on investment. Larrick, Burson, and Soll (2007) found that the degree of individuals overconfident is strongly

associated with their thinking that make them to feel that they are better than average. Overconfident managers

generally prefer to overinvest and the overconfident tends to attract more mergers, starting new firms and initiate more

investment. Similarly, Brown and Sarma (2007) stated that CEO overconfidence affect the frequency of corporate

acquisitions of a firm. If past returns on investment are high, CFOs would become more confident on their estimate o f

future returns. A group of 55 managers working in small firms of computer industry have been studied by Simon and

Houghton (2003). Findings showed that managers with greater overconfidence would prefer to introduce more risky

products and seem to fail many times. In early 1990s, some studies found that managerial overconfidence tends to

innovation (Staw, 1991) and to plant expansion (Nutt, 1993). Glaser, Schafers, and Weber (2008) surveyed senior

managers behavior and they observed that when managers are optimistic, they increase their exposure to firm specific

risk when transaction on invest more and in turn increase investment cash flow sensitivity.

Size of the firm is one of the major determinants in capital budgeting practices (e.g., Ho & Pike, 1992; Graham &

Harvey, 2001; Farragher et al., 2001; Brounen et al., 2004; Verbeeten, 2006). Researches supported that large firms

adopts more innovative capital budgeting methods, say, sophisticated capital budgeting practices, to a large extent than

smaller firms do (e.g., Rogers, 1995; Williams & Seaman, 2001) since the larger firms have the capacity and resources

to use sophisticated capital budgeting practices (Ho & Pike, 1992). Payne et al.(1999) and Ryan and Ryan (2002)

documented that large firms were more inclined to use more sophisticated capital budgeting practices. This is due to the

larger firms involves larger projects and the use of sophisticated capital budgeting practices become less costly (Payne

et al., 1999; Hermes et al., 2007).There was a positive relationship between firm size and the use of DCF methods.

Findings have also been confirmed in Hermes et al.‘s (2007) studies. Trahan and Gitman (1995) connotes that large

companies exploited DCF methods (88 % for NPV and 91 % IRR) than small companies (65% for NPV and 54% for

IRR). It was further confirmed in Segelod‘s (1998) study and he found that major firms uses PB model for evaluating

small investments, however, for the large investment decision at least of the DCF methods is in practice. In 2001,

Graham and Harvey studied about capital budgeting methods and firm size in the U.S. and results showed that there is a

significant negative relationship between size and PB. Brounen et al.(2004) found that company size was positively

correlated with the use of capital budgeting methods, large companies use NPV, IRR, and sensitivity analysis more than

small companies.

majority favored NPV and

IRR.

scenario analysis and

risk-adjusted discount

rate. Use of real options is

limited (8%).

Kester & Robbins

(2011)

18 Chief Financial

Officers of

companies listed

on the Irish Stock

Exchange

More Sophisticated

Discounted Cash Flow

Techniques.

(Weighted Average Cost

of Capital is to evaluate

all proposed capital

investments).

Scenario Analysis and

Sensitivity Analysis

Singh, Jain & Yadav

(2012)

31 listed

Companies (India)

More sophisticated DCF

techniques.

Sensitivity analysis

Maroyi & Pol l (2012) 13 Companies

Listed in the

Mining Sector of

the Johannesburg

Securities

Exchange (JSE).

NPV Real option

Applied Economics and Finance Vol. 3, No. 2; 2016

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Generally, ownership structure has greater influence on any managerial decision making and resultant effect on firm‘s

performance (Warfield,Wild & Wild, 1995; Klassen, 1997). Greater managerial ownership has been identified to be

increased use of recommended capital budgeting methods and thus less likely to experience financial distress (Donker,

Santen & Zahir, 2009). It is oft-reported that what managers actually do they ignore profitability investment (even if it

offers positive NPV), if accounting rate of return is too low, and thus top management willed to sacrifice long term

value to meet accounting targets (Graham, Harvey & Rajgopal, 2005).The ownership sometime classify as listed at the

stock exchange or non listed (Hermes et al., 2007). Listed firms were used accurate estimation of cost of equity ,and

cost of capital and more likely to NPV or IRR than non listed (Hermes et al., 2007).

Nature of the industries were also identified as the determinant of capital budgeting practices, for example financial

services industry and the building, construction and utilities industries, have been interest of using more sophisticated

capital budgeting practices than other industries (Verbeeten, 2006). Further, many empirical researches in the past

showed that capital budgeting practices are different across industries (e.g., Ho & Pike, 1998). For example,

widespread use of real option or game theory are more prevalent in the pharmaceutical industry (e.g., Bowman &

Moskowitz, 2001; McGrath & Nerkar, 2004), the extraction industry (e.g., Trigeorgis, 1993), and the financial services

industry and the high-tech industry (e.g., Billington, Johnson & Triantis, 2003).

Education of CFOs was recognized as the determinant of capital budgeting. There was a general argument that CFO

with higher education has fewer problems in understanding more sophisticated capital budgeting techniques and they

thus have the capacity to use them. For example, in Chinese firms, CFOs with higher level of education use cost of debt

less often in comparison with less educated CFOs. Thus, a positive relationship identified between educational

background of CFOs and the use of sophisticated methods (Hermes et al., 2007). Among the U.S. sample, there was a

positive association has been found between CEO education and use of IRR (Graham & Harvey, 2001) and the findings

has been confirmed in the Netherlands, Germany and France, but not in the UK (Brounen et al., 2004). The reasons for

more widespread use of DCF are the availability of computer software that used in computation (e.g., Pike, 1996) and

increased level of formal education of managers (e.g., Pike, 1996; Sangster, 1993). A few studies found that age of the

CFOs was also a determinant of capital budgeting methods. For example, older CFOs could be reluctant to adopt new

techniques, and instead prefer to relaying on older methods (e.g., Hermes et al., 2007).

Since capital investment involves in long term, uncertainty /risk would play a vital role in capital investment decision

making. Generally, uncertainty refers to as the gap between information available and information required to make any

decision. Complete information is unavailable in long run and thus, uncertainty is the dominant factor in capital

investment (Simerly & Li, 2000; Zhu & Weyant, 2003). Nature and type of uncertainty could be, including raw material

uncertainties, input market uncertainties, labor uncertainties, political uncertainties, production uncertainties, output

market uncertainties, liability uncertainties, interest uncertainties, inflation uncertainties, policy uncertainties, exchange

rate uncertainties, competitive uncertainties and society uncertainties. Uncertainties have been treated with adopting

sophisticated capital budgeting practices, for example, use of ROR and/or GT tools (e.g., Bowman & Hurry, 1993; Zhu

& Weyant, 2003). The main concepts of the ROR demonstrates that specific uncertainties (rather than in general) that

would affect capital budgeting practices (Dixit & Pindyck, 1994). Game theory specifies that the optimal investment

criterion can also be changed by specific uncertainties (Smit, 2003). Thus, specific uncertainties need to be tackled with

using different capital budgeting methods. The research findings supported that sophisticated capital budgeting practices

are crucial and useful if financial uncertainties i.e., exchange rate, interest exist. However, social uncertainties, market

uncertainties, and input uncertainties have not sufficiently supported to influence on use of sophisticated capital

budgeting practices. Rather, theoretical background, many experts in capital budgeting area is expected to offer the

capacity and willingness to adopt contemporary capital budgeting practices (e.g., Libby & Waterhouse, 1996, Williams

& Seaman, 2001). Theory and a few empirical research states that specific uncertainties affect capital budgeting

practices, for example, Ho and Pike (1998) found that there is a positive relationship between socioeconomic

uncertainty (i.e., governmental regulations, trade unions actions) and the application of risk analysis techniques,

however, the empirical evidence on these relationship with sophisticated capital budgeting practices are scarce

(Verbeeten, 2006).

Recognition, assessment and reflection of the risk/uncertainty are intriguing. Nowadays, there are number of risk

analysis method available such as sensitivity analysis, scenario analysis, decision trees, computer simulation and Monte

Carlo analysis. In Graham and Harvey‘s (2001) study, participants recognized market risk and they also reported other

risk factors including interest rate, inflation, size, foreign exchange rate. Surprisingly, they found that at least half of the

firm did nothing to adjust WACC (firm‘s average risk) to incorporate project risk. However, in 1996, Shao and Shao

reported that firms employed more on risk adjusted cash flows than risk-adjusted discount rates. Across their sample,

they found that sensitivity analysis was the principal assessment technique. In contrast, Gitman and Vandenberg (2000)

found in their study that 39 % of firms were adjusting their rates against adjusting risk for cash flows. Through there are

number of sophisticated risk analysis models available, the applicability of those models were prone to barriers. The

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reasons for their reluctant have been reported as; it is not practical, depending on unrealistic assumption, difficulties in

explaining to the top management and the difficulties in applying (Trahan & Gitman, 1995). Notwithstanding progress

in risk identification, assessment and adjustment has been reported, none of the studies have not been looked at actual

risk analysis, its process and management inputs to improve or usage of existing risk assessment and adjustment models.

Sophisticated capital budgeting practices would help to identify many different types of investment projects in terms of

uncertainty.A range of risk across the many investment projects would create diversification. Diversification generally

helps to maximize the income from investments at minimum risk. A positive relationship has been found between

diversification and use of sophisticated capital budgeting practices (Verbeeten, 2006). Recently, Holmen and Pramborg

(2009) reported that the use of payback method has been positively combined with political risk.

Klammer (1993), and Shank and Govindarajan (1992) suggested that nonfinancial consideration have been integrated

into capital budgeting practices. For example, corporate management integrated into capital budgeting and thus the

decision depends on some of the strategic management tools such as value chain analysis, cost drivers analysis, and

completive advantage analysis. According to Carr and Tomkins (1996), the most successful companies were found to

be using nonfinancial strategic information in making investment decision among their sample of 51 case studies in the

UK, the U.S., and the German companies. However, it is argued that nonfinancial methods were prevalence when the

firms did not adequately implement DCF methods (Carr &Tomkins 1996). However, any studies have not been carried

out the use of non financial methods linking to DCF analysis. It has been argued that increasing acceptance of DCF

analysis ignores the use of nonfinancial methods (e.g., Graham & Harvey 2001; Ryan &d Ryan, 2002).

Capital budgeting practices are different and may have ―country effect‖ influence. This can be attributed to the some

level of economic factors that determine choice of capital budgeting practices. It is recommend furthering research in

indentifying country effect on capital budgeting practices with respect to the level of economic, human, financial and

technological improvement. Shahrokh (2002) argued that capital budgeting is very complex, determined by many

factors including: terminal values, foreign currency fluctuations, long-term inflation rates, subsidized financing, and

Political risk. In Sekwat‘s (1999) study of capital budgeting practices in Tennessee municipal governments, the decision

in using capital budgeting techniques are based on simple, versatile and flexibility of those techniques. Notwithstanding,

he further argued that the usage of techniques in practices is in conjunction with qualitative factors such as ethical, legal,

or political considerations. He concluded that since government funds the capital projects, political factors plays a

critical role in making capital investment decisions.

3.8 Disparities between capital budgeting theory and practices

Capital budgeting theory recommends in using DCF methods (NPV, IRR, MIRR, PI and DPB) and non DFC methods

(PB and ARR) for making capital budgeting decision. However, all most all the firms in developed and developing

countries inclined to use sophisticated capital budgeting methods along with many capital budgeting tools for

incorporating risk (i.e., sensitivity analysis, real options) and sophisticated discounted rate (i.e., Weighted Average Cost

of Capital, Cost of Debt, CAPM) (e.g., Arnold & Hatzopoulos, 2000; Graham & Harvey, 2001; Ryan & Ryan, 2002;

Cooper et al., 2002; Brounen et al., 2004; Hermes et al.,2007; Bennouna et al., 2010; Maquieira , Preve and Allende,

2012).

Nemours factors have been identified as the determinant of capital budgeting during the last two decades including size

of the firm, ownership structure, nature of industries, educational qualification of CFOs, experience of CFOs, age of

CFOs, uncertainty(for example, interest rate, inflation, foreign exchange rate), nonfinancial consideration and other

factors (i.e, economic, human, technology, finance, ethical and political). Among them, some factors (for example, size

of the firm, educational qualification of CFOs, experience of CFOs, age of CFOs) were positively associated with the

use of sophisticated capital budgeting practices. However, in some cases, economic, political and technological factors

directly and indirectly affect choice of the capital budgeting practices. (e.g., Bowman & Moskowitz, 2001; Zhu &

Weyant, 2003; McGrath & Nerkar, 2004; Verbeeten, 2006; Donker et al., 2009). Moreover, the factors determining

capital budgeting practice connotes that to certain extent capital budgeting practice prone to ‗country effect infl uence‘,

for example economic factor, cutting edge technology (i.e., decision support system), political factors, accounting

policies, accounting standards and other infrastructure facilities. Although capital budgeting theory was applicable

regardless of countries, to certain extent the actual practices of capital budgeting (for example selection of capital

investment) vary (e.g., Graham & Harvey, 2001; Shahrokh ,2002).‗In practice uncertainty, information asymmetry,

multiple (conflicting) objectives, real options and multi -period multi project considerations greatly complicate capital

budgeting beyond the focus of the theory‘ (Arnold & Hatzopoulos, 2000, p.609). A consideration of the impact of

information asymmetry, real options and other complications on the capital budgeting exercise gives one the view that

there is no unique correct technique and that there is a need for multiple methods (Arnold & Hatzopoulos, 2000). Thus,

all these factors impinge on choice of the capital budgeting practices, and consequently, there are disparities between

theory and practices.

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Studies on the practice of capital budgeting in many countries have found that firms increasingly employ more

sophisticated capital budgeting techniques to make investment decisions over several years (Klammer, 1973; Klammer

& Walker, 1984; Pike, 1988; Klammer, Koch & Wilner, 1991; Jog & Srivastava, 1995; Gilbert & Reichart, 1995;

Farragher et al., 1999;Arnold & Hatzopoulos, 2000; Graham & Harvey, 2001; Mustapha & Mooi, 2001; Ryan & Ryan,

2002; Brounen et al., 2004; Hermes et al., 2007; Truong et al., 2008; Baker et al., 2011; Singh et al., 2012). When

comparing a developed economy with an emerging economy, the developed economy has highly developed capital

markets with high levels of liquidity, meaningful regulatory bodies, large market capitalization, and high levels of per

capita income (Geary, 2012). An emerging market is in the process of rapid growth and development with lower per

capita income, less mature capital markets and very small capital projects, compared with developed countries. Therefore,

obviously, emerging market economies pose challenges in applying capital budgeting techniques, owing to less

developed capital markets and the difficulty of setting key parameters.

3.9 Answering to the research questions: Summary of the findings

It is crucial to answer the research questions in order to attain research aims. The first question enquired about ―what are

the capital budgeting theories and practices used by firms? Are there any disparities between the capital budgeting

theories and practices? If so how?‖ The answers for these questions have been well documented during the last twenty

years of studies. Capital budgeting theory recommends in using DCF methods (NPV, IRR, MIRR, and DPB) and non

DFC methods (PB and ARR) for making capital budgeting decision. However, all most all the firms in developed and

developing countries inclined to use sophisticated capital budgeting methods along with many capital budgeting tools

for incorporating risk (i.e., sensitivity analysis, real options) and sophisticated discounted rate (i.e., WACC, CD, CAPM)

(e.g., Arnold & Hatzopoulos, 2000; Graham & Harvey, 2001; Ryan & Ryan, 2002; Cooper et al., 2002; Brounen et al.,

2004; Hermes et al., 2007; Bennouna et al., 2010; Maquieira et al., 2012). Thus it can be concluded that there are

some disparities between capital budgeting theory and practice. The next research‘s question further backs up to this

question.

The second question asked about ―what are the factors determines the use of capital budgeting practices? Are there

different across countries? If so how?‖ Nemours factors have been identified as the determinant of capital budgeting

during the last two decades including size of the firm, ownership structure, nature of industries, educational

qualification of CFOs, experience of CFOs, age of CFOs, uncertainty(for example, interest rate, inflation, foreign

exchange rate), nonfinancial consideration and other factors (i.e, economic, human, technology, finance, ethical and

political). Among them, some factors (for example, size of the firm, educational qualification of CFOs, experience of

CFOs, age of CFOs) were positively associated with the use of sophisticated capital budgeting practices. However, in

some cases, economic, political and technological factors directly and indirectly affect choice of the capital budgeting

practices. (e.g., Bowman & Moskowitz, 2001; Zhu & Weyant, 2003; McGrath & Nerkar, 2004; Verbeeten, 2006;

Donker et al.,2009). Moreover, the factors determining capital budgeting practice connotes that to certain extent capital

budgeting practice prone to ―country effect influence‖, for example economic factor, cutting edge technology (i.e.,

decision support system), political factors, accounting policies, accounting standards and other infrastructure facilities.

Although capital budgeting theory was applicable regardless of countries, to certain extent the actual practices of capital

budgeting (for example selection of capital investment) vary (e.g., Graham & Harvey, 2001; Shahrokh , 2002). Thus, all

these factors impinge on choice of the capital budgeting practices, and consequently, there are disparities between

theory and practices.

The last question asked about ―what are the gaps in the existing capital budgeting literature?‖ Traditional financial

theory suggests that the decision makers are rational, however, modern theory suggests that decision have influenced by

many cognitive illusions (Leon et al., 2008; Tayib & Hussin, 2011). Thus behavioral finance came into play in capital

budgeting decision making. Capital budgeting research connected with behavioral finance have not been studied any

developing countries during the last twenty years. Literature says behavioral finance is a dominant theory determining

capital budgeting decision, confirmed in many studies carried out in developed countries. Thus, there is a complete

dearth of research in Asian studies in case of behavioral finance penetration on capital budgeting practices.

No studies have been attempted to identify relationship between supportive capital information system (software

products to make the required analysis easier in comparison with manual system) and capital budgeting decision

making. Thus it has been identified as a gap between information system and choice and practice of capital budgeting

(Bennouna et al., 2010). Similarly, the environment in which organization are working impact on quality decision. Thus,

researcher should concentrate on scanning organizational environment to make good investment decision rather purely

depends on financial theory. Thus it is paramount important in the current context.

Almost all the research carried out during the last two decades adopted limited methodological aspects. For example,

cross sectional research design, case study and some form of qualitative study were more popular (e.g., Butler et al.,

1993; Verbeeten, 2006; Hermes et al.,2007; Maquieira et al., 2012). However, in modern world, some form of event

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study methodology would be seminal for providing greater insights into capital budgeting practices. Thus, a gap has

been identified in use of methodological concepts.

Renowned researchers found that nowadays most of the large companies are inclined to use sophisticated capital

budgeting practices. However, it is intriguing question whether SCBP are important to all types of investment (e.g.

expansion, replacements, mergers and takeovers) and all type of industries, and those techniques outperform than non

SCBP. Thus, these conundrums need to be well investigated.

Many research scholars have argued that capital budgeting influenced by ―country effect influence‖ (e.g., Graham &

Harvey, 2001; Shahrokh, 2002; Hermes et al., 2007), for example, economic policies, taxation system, accounting

policies, conductive social climate, culture of people, technological factor (i.e., decision support system), government

control, political factors, infrastructure facilities. Therefore, more extensive studies are imperative from unsearched

countries to build robust knowledge.

Many studies conducted in developed counties have found that firms use more sophisticated capital budgeting practices

(Graham & Harvey, 2001; Brounen et al.,2004). Nonetheless, when comparing with developed countries, more

sophisticated capital budgeting practices are not prevalent in developing countries. Thus, future research scholars need

to consider the challenges faced by CFOs with regard to the use of sophisticated capital budgeting practices (i.e.

organizational barriers/knowledge gap of CFOs, technological challenges) as they lead to increased performance.

Another opportunity for future research is the investigation of other organizational characteristics (e.g. business unit

strategies, reward and incentive structures, distribution of decision rights and financial structure) that have been shown

to affect capital budgeting practices. Renowned researchers have found that nowadays, most large companies are

inclined to use sophisticated capital budgeting practices (SCBP).

3.10 Policy recommendation

Many research scholars criticized that many researches on capital budgeting were opt-testing the methods of capital

budgeting and its practices. They were purely finding that actual what methods were in practice. However, in practice,

there are enormous factors affecting the capital budgeting practice and it has ―country effect‖ too. In line up with this

argument, this research was well thought out in its design and become springboard for future research. This study

contributed by stating the known and unknown arena of capital budgeting during the last two decades.

In the cutting edge technology world, the way of doing things have been changed and challenging. For example,

decision support system become more prevent in making decision and more advanced technological sphere penetrates

into assessing capital budgeting practices than ever before. Thus, this research would make awareness to top

management, policy makers, practitioners and stakeholders of the company.

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