Review of Business and Economics Studies, 2014, том 2, № 3
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Review of Business and Economics Studies EDITOR-IN-CHIEF Prof. Alexander Ilyinsky Dean, International Finance Faculty, Financial University, Moscow, Russia ailyinsky@fa.ru EXECUTIVE EDITOR Dr. Alexander Kaffka EDITORIAL BOARD Dr. Mark Aleksanyan Adam Smith Business School, The Business School, University of Glasgow, UK Prof. Edoardo Croci Research Director, IEFE Centre for Research on Energy and Environmental Economics and Policy, Università Bocconi, Italy Prof. Moorad Choudhry Dept.of Mathematical Sciences, Brunel University, UK Prof. David Dickinson Department of Economics, Birmingham Business School, University of Birmingham, UK Prof. Chien-Te Fan Institute of Law for Science and Technology, National Tsing Hua University, Taiwan Prof. Wing M. Fok Director, Asia Business Studies, College of Business, Loyola University New Orleans, USA Prof. Konstantin P. Gluschenko Faculty of Economics, Novosibirsk State University, Russia Prof. George E. Halkos Associate Editor in Environment and Development Economics, Cambridge University Press; Director of Operations Research Laboratory, University of Thessaly, Greece Dr. Christopher A. Hartwell President, CASE - Center for Social and Economic Research, Warsaw, Poland Prof. S. Jaimungal Associate Chair of Graduate Studies, Dept. Statistical Sciences & Mathematical Finance Program, University of Toronto, Canada Prof. Bartlomiej Kaminski University of Maryland, USA; Rzeszow University of Information Technology and Management, Poland Prof. Vladimir Kvint Chair of Financial Strategy, Moscow School of Economics, Moscow State University, Russia Prof. Alexander Melnikov Department of Mathematical and Statistical Sciences, University of Alberta, Canada Prof. George Kleiner Deputy Director, Central Economics and Mathematics Institute, Russian Academy of Sciences, Russia Prof. Kwok Kwong Director, Asian Pacific Business Institute, California State University, Los Angeles, USA Prof. Dimitrios Mavrakis Director, Energy Policy and Development Centre, National and Kapodistrian University of Athens, Greece Prof. Steve McGuire Director, Entrepreneurship Institute, California State University, Los Angeles, USA Prof. Rustem Nureev Head of the Department of Macroeconomics, Financial University, Russia Dr. Oleg V. Pavlov Associate Professor of Economics and System Dynamics, Department of Social Science and Policy Studies, Worcester Polytechnic Institute, USA Prof. Boris Porfiriev Deputy Director, Institute of Economic Forecasting, Russian Academy of Sciences, Russia Prof. Svetlozar T. Rachev Professor of Finance, College of Business, Stony Brook University, USA Prof. Boris Rubtsov Chair of Financial Markets and Financial Engineering, Financial University, Russia Dr. Minghao Shen Dean, Center for Cantonese Merchants Research, Guangdong University of Foreign Studies, China Prof. Dmitry Sorokin Deputy Director, Institute of Economy, Russian Academy of Sciences, Head of the Department of Macroeconomics Regulation, Financial University, Russia Prof. Robert L. Tang Vice Chancellor for Academic, De La Salle College of Saint Benilde, Manila, The Philippines Dr. Dimitrios Tsomocos Saïd Business School, Fellow in Management, University of Oxford; Senior Research Associate, Financial Markets Group, London School of Economics, UK Prof. Sun Xiaoqin Dean, Graduate School of Business, Guangdong University of Foreign Studies, China REVIEW OF BUSINESS AND ECONOMICS STUDIES (ROBES) is the quarterly peerreviewed scholarly journal published by the Financial University under the Government of Russian Federation, Moscow. Journal’s mission is to provide scientific perspective on wide range of topical economic and business subjects. CONTACT INFORMATION Financial University Leningradskiy Av. 51 Building 3, 125993 Moscow Russian Federation Telephone: +7(499) 943-95-23 Website: www.robes.fa.ru AUTHOR INQUIRIES Inquiries relating to the submission of articles can be sent by electronic mail to robes@fa.ru. COPYRIGHT AND PHOTOCOPYING © 2014 Review of Business and Economics Studies. All rights reserved. No part of this publication may be reproduced, stored or transmitted in any form or by any means without the prior permission in writing from the copyright holder. Single photocopies of articles may be made for personal use as allowed by national copyright laws. ISSN 2308-944X
Вестник исследований бизнеса и экономики ГЛАВНЫЙ РЕДАКТОР А.И. Ильинский, профессор, декан Международного финансо вого факультета Финансового университета ВЫПУСКАЮЩИЙ РЕДАКТОР А.В. Каффка РЕДАКЦИОННЫЙ СОВЕТ М. М. Алексанян, профессор Бизнесшколы им. Адама Смита, Университет Глазго (Великобритания) К. Вонг, профессор, директор Института азиатско-тихоокеанского бизнеса Университета штата Калифорния, Лос-Анджелес (США) К. П. Глущенко, профессор Экономического факультета Новосибирского госуниверситета С. Джеимангал, профессор Департамента статистики и математических финансов Университета Торонто (Канада) Д. Дикинсон, профессор Департамента экономики Бирмингемской бизнесшколы, Бирмингемский университет (Великобритания) Б. Каминский, профессор, Мэрилендский университет (США); Университет информационных технологий и менеджмента в Жешове (Польша) В. Л. Квинт, заведующий кафедрой финансовой стратегии Московской школы экономики МГУ, профессор Школы бизнеса Лассальского университета (США) Г. Б. Клейнер, профессор, член-корреспондент РАН, заместитель директора Центрального экономико-математического института РАН Э. Крочи, профессор, директор по научной работе Центра исследований в области энергетики и экономики окружающей среды Университета Боккони (Италия) Д. Мавракис, профессор, директор Центра политики и развития энергетики Национального университета Афин (Греция) С. Макгвайр, профессор, директор Института предпринимательства Университета штата Калифорния, Лос-Анджелес (США) А. Мельников, профессор Департа мента математических и статистических исследований Университета провинции Альберта (Канада) Р. М. Нуреев, профессор, заведующий кафедрой «Макроэкономика» Финансового университета О. В. Павлов, профессор Депар тамента по литологии и полити ческих исследований Ворчестерского политехнического института (США) Б. Н. Порфирьев, профессор, член-корреспондент РАН, заместитель директора Института народнохозяйственного прогнозирования РАН С. Рачев, профессор Бизнес-колледжа Университета Стони Брук (США) Б. Б. Рубцов, профессор, заведующий кафедрой «Финансовые рынки и финансовый инжиниринг» Финансового университета Д. Е. Сорокин, профессор, член-корреспондент РАН, заместитель директора Института экономики РАН, заведующий кафедрой «Макроэкономическое регулирование» Финансового университета Р. Тан, профессор, проректор Колледжа Де Ла Саль Св. Бенильды (Филиппины) Д. Тсомокос, Оксфордский университет, старший научный сотрудник Лондонской школы экономики (Великобритания) Ч. Т. Фан, профессор, Институт права в области науки и технологии, национальный университет Цин Хуа (Тайвань) В. Фок, профессор, директор по исследованиям азиатского бизнеса Бизнес-колледжа Университета Лойола (США) Д. Е. Халкос, профессор, Университет Фессалии (Греция) К. А. Хартвелл, президент Центра социальных и экономических исследований CASE (Польша) М. Чудри, профессор, Университет Брунеля (Великобритания) Сун Цяокин, профессор, декан Высшей школы бизнеса Гуандунского университета зарубежных исследований (КНР) М. Шен, декан Центра кантонских рыночных исследований Гуандунского университета (КНР) Издательство Финансового университета 125993, Москва, ГСП-3, Ленинградский проспект, 51, корп. 3, к. 104. Тел. 8 (499) 943-95-23. Интернет: www.robes.fa.ru. Журнал «Review of Business and Economics Studies» («Вест ник исследований бизнеса и экономики») зарегистрирован в Федеральной службе по надзору в сфере связи, информационных технологий и массовых коммуникаций 9 июля 2013 г. Свидетельство о регистрации ПИ № ФС77-54658. Подписано в печать: 19.09.2014. Формат 60 × 84 1/8. Заказ № 92 от 19.09.2014. Отпечатано в ООП Издательства Финуниверситета (Настасьинский пер., д. 3, стр. 1). 16+
CONTENTS Behavioral Biases in Capital Budgeting: An Experimental Study of the Effects on Escalation of Commitment Given Different Capital Budgeting Methods Dennis Gnutek 5 Moscow Energy Strategy in the Framework of the Russian Energy Strategy Dmitry Tidzhiev 20 Investing in War: Empirical Evidence of Investors’ Unsustainable Behavior in Times of Armed Conflict Esmira Safarova 46 Productivity Spillovers in the Russian Federation: The Case of Chemical Market Anastasia Kuzyaeva, Alexander Didenko 55 Innovations as Factor of Absorptive Capacity of FDI Spillovers across Regions of Russian Federation Alexander Didenko, Tatiana Egorova 75 A Structural Model of Exchange Rate Dynamics Anton Kuzmin 86 Prioritization of Russian Regions for Sustainable Investing Purposes Using Data Envelopment Analysis Anastasia Arkhipova 93 Review of Business and Economics Studies Volume 2, Number 3, 2014
CОДЕРЖАНИЕ Поведенческие отклонения в бюджетировании капитала: экспериментальное исследование эффектов эскалации обязательства с учетом различных методов бюджетирования Деннис Гнутек 5 Московская энергетическая стратегия в рамках энергетической стратегии России Дмитрий Тиджиев 20 Инвестиции в войну: эмпирический анализ поведения инвесторов в периоды вооруженных конфликтов Эсмира Сафарова 46 Влияние прямых иностранных инвестиций на рост производительности на примере российского рынка химического сырья Анастасия Кузяева, Александр Диденко 55 Исследование инноваций как фактора прямых иностранных инвестиций в регионах Российской Федерации Александр Диденко, Татьяна Егорова 75 Структурная модель динамики валютного курса Антон Кузьмин 86 Анализ инвестиционной привлекательности российских регионов методом DEA Анастасия Архипова 93 Вестник исследований бизнеса и экономики № 3, 2014
Review of Business and Economics Studies Volume 2, Number 3, 2014 Behavioral Biases in Capital Budgeting: An Experimental Study of the Effects on Escalation of Commitment Given Different Capital Budgeting Methods* Dennis Gnutek School of Business, Economics and Law, Gothenburg University, Sweden dennisgnutek_89@hotmail.com Abstract. This study examines if decision-makers using less sophisticated capital budgeting methods, such as Net present value and Payback, display a higher level of escalation of commitment to a failing project, compared to decision-makers using more sophisticated capital budgeting methods, such as Real options. Past studies advocates superiority in decision-making when incorporating more sophisticated models into a company’s capital budgeting. The findings coincide with previous studies; that decision-makers explicitly using Real options display a lower escalation of commitment compared to decision-makers using Net present value. However, no difference in escalation of commitment was recorded between decision-makers using Payback and decisionmakers using Real options. Аннотация. Это исследование рассматривает особенности использования более простых методов бюджетирования капитала — таких как чистая приведенная стоимость и окупаемость — в сравнении с более сложными методами, такими как реальные опционы. Предшествующие исследования доказывают преимущества использования более сложных моделей при принятии решений. Результаты совпадают с предыдущими исследованиями: руководители, использующие в явном виде реальные опционы, показывают меньший рост эскалации обязательства по сравнению с теми, кто принимал решения на основе чистой приведенной стоимости. Однако разницы в эскалации обязательства не было отмечено между руководителями, принимающими решения на основе метода окупаемости, и теми, кто использовал реальные опционы. Key words: Real options, Net present value, Payback, capital budgeting, escalation of commitment. * Поведенческие отклонения в бюджетировании капитала: экспериментальное исследование эффектов эскалации обязательства с учетом различных методов бюджетирования. 1. INTrODuCTION This study examines if decision-makers using less sophisticated capital budgeting methods, such as Net present value and Payback, display a higher level of escalation of commitment to a failing project, compared to decision-makers using more sophisticated capital budgeting methods, such as Real options. The definition of escalation of commitment is when decision-makers continue to dedicate resources to a failing project influenced by previously invested resources (Staw, 1976). In previous research, Denison (2009) conducted an experiment testing the effects of escalation of commitment to a failing course of action, by comparing investment recommendations between participants using explicitly Net present value and Real options. Denison’s results of the experiment indicated that participants using Real options were less likely to exhibit escalation of commitment compared to participants using Net present value, and were also more likely to abandon unprofitable projects. Advocates arguing to incorporate Real options in capital budgeting claim that more sophisticated capital budgeting leads to superior decision-making compared to less sophisticated capital budgeting methods (Antikarov and Copeland, 2001). The superiority of sophisticated capital budgeting methods derives from the higher quality of information being available to the decision-makers (Denison, 2009). Less sophisticated capital budgeting methods, such
Review of Business and Economics Studies Volume 2, Number 3, 2014 as discounted cash flow models, serve as appropriate valuation methods for cash cow businesses, but fall short when implementing substantial growth opportunities, R&D expenditure, intangible assets and abandonment value in valuation analysis (Myers, 1984). With discounted cash flow models understating the option value attached to growing, profitable businesses (Myers, 1984), the information used in these methods is presumed inferior to the information used in real options analysis. Studies have claimed that by exclusively using Real options analysis, the option of project abandonment becomes more cognitively accessible to decision-makers (Denison, 2009), and helps overcome “antifailure bias” (McGarth, 1999). This would suggest that decision-makers using Real options in their capital budgeting would be likely to display a lower level of escalation of commitment in failing projects compared to decision-makers using Net present value and Payback. Regardless of theoretical superiority of incorporating a higher sophistication in capital budgeting, empirical findings suggest that in real life, managers oppose incorporating real options into capital budgeting (see Pike, 1996; Graham and Harvey, 2001; Sandahl and Sjögren, 2003; Block, 2007; Brunzell, Liljeblom and Vaihekoski, 2011). Block’s (2007) findings suggest that inadequate understanding of real options in top management, and not wanting to shift decision-making to mathematicians and decision scientists, makes managers oppose the usage of real options, and instead rely on discounted cash flow and payback models, which they understand. Irrational behavior due to escalation of commitment exists according to Friedman et al(2007) in the real world on a grand scale. Decision-makers justify continuous resource spending into failing projects with the amount of resources already been spent, instead of considering abandonment. A few real world examples of escalation of commitment behavior can be illustrated with the Coke and Pepsi wars, Campeau auction, Maxwell Нouse and Folgers advertising war and NASA’s space shuttle Columbia, all resulting in an unnecessary spending of resources (Friedman et al., 2007). If instead decision-makers would become aware of the irrational behavior because of the escalation of commitment bias, it could potentially prevent project cost overruns. The purpose of this paper is to examine if more sophisticated capital budgeting methods lead to lower escalation of commitment, thereby preventing project cost overruns and leading to more profitable investment decisions. To answer the research question, an experiment was conducted in which participants used one of three capital budgeting methods: Real options, Net present value, or Payback. By evaluating a project using the assigned capital budgeting method, the participants’ recommendations to continue an unprofitable project were measured. Since in the experiment, a uniform decision should have been made regardless of capital budgeting method used, deviating behavior between capital budgeting methods was due to behavioral effects. The difference between this study and previous studies (see Denison, 2009) is the inclusion of the capital budgeting method Payback. Payback is included in this study because of its historically persistent extensive use in capital budgeting (see Pike, 1996; Graham and Harvey, 2001; Sandahl and Sjögren, 2003; Brunzell, Liljeblom and Vaihekoski, 2011), and low sophistication. The findings in this paper indicate that participants using Real options were not only more aware of a potential project failure compared to Net present value and Payback participants, but were also more likely to abandon a failing project compared to Net present value participants. However no difference was recorded in the likelihood of project abandonment between participants explicitly using Real options compared to participants explicitly using Payback. The lower escalation of commitment in Real options compared to Net present value participants was recorded even though all participants were provided the same information about cash flows, abandonment value and sunk costs. The remainder of this paper is structured as follows. Section 2 presents relevant literature related to the behavioral biases escalation of commitment and sunk cost fallacy, followed by a review of the three capital budgeting methods used in the experiment. Section 3 formulates and presents the hypothesis. Section 4 describes the methodology of the experiment and statistical methods used. Section 5 presents and analyzes the results of the experiment, provides limitations of the study and concluding remarks. 2. ThEOry 2.1. BACKGrOuND Expected utility theory (EUT) suggests that rational investors pursue utility maximization in their investments. In 1979 Daniel Kahneman and Amos Tversky found human behavior violating the axioms of EUT, and proposed an alternative model for determining decision-making under risk. Kahneman and Tversky’s (1979) prospect theory motivates that a person’s behavior is changing depending on if the person is winning or losing. If a person is winning (situated in the
Review of Business and Economics Studies Volume 2, Number 3, 2014 gain domain) the person will display risk aversion behavior (favor certainty before uncertainty), while if the person is losing (situated in the loss domain) the person will display risk seeking behavior (favor uncertainty before certainty). Further research based on prospect theory (see Thaler, 1980; Statman and Caldwell, 1987) developed behavioral theories such as mental accounting, behavior enhanced with emotions of pride/regret and escalation of commitment, which all influence abandonment decisions in executive management. Statman and Caldwell (1987) argued, based on Kahneman and Tversky’s idea, that: “Behavioral finance provides a framework, supported by experiments, that is consistent with the tendency to resist project termination”. Managers opposing project abandonment will overinvest in projects, thereby diverging from profit maximization decisions. The two main behavioral biases discussed in this paper, which influence abandonment decisions, are Escalation of commitment and Sunk cost fallacy. Both behavioral biases emerge from mental accounting, introduced by Thaler (1980) and exemplified by Statman and Caldwell (1987). 2.2. MENTAl ACCOuNTING While making decisions of abandonment or continuation, managers are faced with making choices based on uncertain cash flows. Managers that follow the net present value analysis, frame the cash flows according to economic accounting (Statman and Caldwell, 1987). But instead of using economic accounting managers use mental accounting to frame future cash flows, thereby including sunk costs in their decision-making (Statman and Caldwell, 1987). Kahneman and Tversky’s (1979) prospect theory divides the decision-making process into two phases. Firstly the manager frames the project by establishing mental accounts. Secondly the manager evaluates the project given the mental accounts created. Consider the following example: A project has lost $2,000 and the manager is given two options: 1) Continue the project with equal probability to gain $2,000 or gain nothing. 2) Abandon the project and gain $1,000 for sure. Depending on if the manager ignores the sunk costs or not, it will either put the manager in the loss domain (include sunk costs) or gain domain (ignore sunk costs) of the value function. According to economic accounting the initial loss of $2,000 should be considered a sunk cost, meaning that the account should be closed with a realized loss of $2,000. The options should then be considered as a 50–50 gamble of $2,000 or nothing for alternative 1, or $1,000 for sure for alternative 2. According to prospect theory a person displays risk aversion behavior in the gain domain (if ignoring sunk costs), and option 2 should therefore be chosen, as certainty is favored before uncertainty. Conversely, if the manager is reluctant to realize losses, the first account will not be closed but instead it will be evaluated with the two options. When including sunk costs in the decision-making, the manager frames the alternatives in the loss domain of the value function. This leads the manager to frame the options as either a sure loss of $1,000 if option 2 is chosen, or a 50–50 gamble of outcome 0 or a loss of $2,000 if option 1 is chosen. According to prospect theory people are reluctant to realize sure losses and will instead display risk-seeking behavior in the loss domain in hopes of turning the loss into a gain or at least to get even. This type of behavior usually leads to even greater losses and was named “get-evenitis” by Shefrin (1999), and defines the behavior of holding on to a failing investment in hopes of getting even. 2.3. BIASES AND hOw ThEy rElATE TO ExIT STrATEGIES Kahneman and Tversky’s (1979) prospect theory and Statman and Caldwell’s (1987) mental accounting theory provide explanations to behavioral biases displayed by managers in project termination decisions. Horn et al(2006) divides the decision-making process for project termination into three steps: An analysis step, a decision step and a step to proceed Figure 1. 3-step decision-making process for project termination by Horn et al. (2006) including behavioral biases. In the first step the company analyzes if their projects are meeting expectations or not. If not, in the second step the company decides if they should terminate the project or continue with it. If a termination decision occurs, in the third step, the executive management works out the details around the project termination (for example the price of the project if it will be sold).
Review of Business and Economics Studies Volume 2, Number 3, 2014 with the abandonment. In Figure 1 the three steps toward project termination and behavioral biases affecting each corresponding step are presented. This study focuses on step 2, the decision step of project termination, and the effects of the behavioral biases escalation of commitment on project abandonment decisions. 2.3.1. Escalation of commitment and sunk cost fallacy “Escalation of commitment and the sunk cost fallacy are essentially the same phenomenon: both lead decision-makers to exaggerate investments following previous commitment of resources. One distinction is that escalation may be associated with forms of commitment other than previous expenditures of economic resources, or sunk costs” (Camerer and Weber, 1999). According to Statman and Caldwell (1987) commitment has both positive and negative behavioral sides in people. The positive side of commitment according to Statman and Caldwell (1987) is the persistence in pursuing goals, a motivator to work harder and accomplish more, and also to generate the force needed to complete difficult projects. Conversely commitment also entraps people in losing projects. When evaluating a project, a manager committed to the project will take all costs into consideration when making the decision to abandon the project or not. In fact, variables such as sunk costs should be disregarded from the calculations. Statman and Caldwell (1987) argue that the tendency to become committed is deeply rooted in us, and that we lack a mechanism to turn it off or regulate it. Few studies have been made examining the effects of capital budgeting methods on escalation of commitment, and if different capital budgeting methods result in a diverging level of escalation of commitment. Denison (2009) found indications of more sophisticated capital budgeting models, like real options (RO), resulting in a lower level of escalation of commitment in failing projects compared to less sophisticated capital budgeting models, like net present value. The effects of different capital budgeting methods on escalation of commitment are unclear, and apart from Denison’s study, no other studies have examined the direct effects of capital budgeting methods on escalation of commitment. 2.4 Capital Budgeting A variety of methods and techniques are available for managers to alleviate capital budgeting procedures (Horngren, Foster, and Datar, 1997). The use of these capital budgeting methods and techniques deviate between different managers (Brijlal, Quesada, 2011), or are by some ignored altogether in the decisionmaking process (McDonald, 2000). But over the past 3 decades companies have started to realize the importance of incorporating the possibility of project failure in capital budgeting decisions (Pike, 1996), thereby beginning to use more sophisticated capital budgeting methods to a higher extent. Some researchers argue that a higher degree of sophistication leads to optimal investment strategies (see Lander and Pinches, 1998; Block, 2007; Antikarov and Copeland, 2001), primarily by using RO. Other studies contradict the theory of more sophisticated capital budgeting methods being superior by arguing, “Empirical research has provided some, but very limited, support for the real-world applicability of real options models” (Chance and Peterson, 2002). Regardless of the theoretical superiority of using RO in capital budgeting, in practice companies seem to continue using Payback (PB) and Net present value (NPV) as their main capital budgeting methods (see Pike, 1996; Graham and Harvey, 2001; Sandahl and Sjögren, 2003; Brunzell, Liljeblom and Vaihekoski, 2011). Block (2007) argues that sophisticated capital budgeting methods like RO are rarely used apart by certain industries such as, technology, energy, and utilities, where management is composed of specialists in science and math. A brief description of each of the capital budgeting methods used in the experiment is provided in the following section. 2.4.1 Payback Payback is a simplistic method calculating the number of periods required to pay back the net investment. A shorter PB period is considered superior to a longer one, since it allows the resources to be reused more quickly (Farris et al., 2010). Academic literature has repeatedly illustrated problems associated with simple capital budgeting techniques such as PB, as it leads to non-firm value maximization investment decisions (Hatfield et al, 2011). The 2 main problems emerging from PB analysis in capital budgeting, are that firstly it neglects time value of money, and secondly that it disregards cash flows generated by the investment after the PB period. A common problem with PB analysis is that projects with a high cash flow in the beginning of the project are preferred, because of a shorter PB ratio, to projects with stable cash flows over a long period of time, regardless of their discounted cash flow value. If projects with lower value are chosen because of their shorter PB ratio, the company is not maximizing shareholder value. Regardless of the critique, the
Review of Business and Economics Studies Volume 2, Number 3, 2014 usage of these simple methods is justified by easily interpreted results and calculations, requiring little or no knowledge in finance (Bower and Lessard as cited in Hatfield et al, 2011). No research has been made examining the relationship between PB and behavioral biases such as escalation of commitment. However, assuming PB being a hurdle rate whether to accept a project or reject it, research claims that self set hurdle rates by decision-makers result in lower escalation of commitment, compared to organization set hurdle rates (Cheng et al, 2003). An approach to decrease escalation of commitment in decision-makers that use the capital budgeting method payback would be to let the decisionmaker set his own hurdle rate for when a project should be accepted or rejected (Statman and Caldwell, 1987; Cheng et al, 2003). 2.4.2 Net present value Net present value incorporates time value of money and presents the difference between the sum of discounted cash inflows and the sum of discounted cash outflows. Therefore if NPV is positive the project should be undertaken, whereas if NPV is negative the project should be abandoned. Variations of NPV calculations also take into account the abandonment value often comparing it to the NPV of the cash flows to determine if a project should be continued or abandoned (Denison, 2009). If the NPV of cash flows is greater (lower) than the abandonment value, the project should be undertaken (abandoned). This NPV variation resembles real options valuation discussed further below. Literature suggests that NPV in theory is superior to other capital budgeting methods, since it consistently chooses the projects that maximize firm value and thereby shareholders’ wealth (Hatfield et al, 2011). Primary critique against NPV is that contrary to RO it does not take into account managerial flexibility in project valuation and assumes the cash flows being fixed. This undervalues the projects by not taking into consideration the options value. Past research claims that decision-makers using NPV in capital budgeting display a higher level of escalation of commitment compared to decision-makers using RO. The higher level of escalation of commitment from using NPV derives from the inferior quality of information available to decision-makers (Denison, 2009). Myers (1984) argues that the type of information used in NPV valuations neglects the value of abandonment, growth opportunities and intangible assets. Neglecting the abandonment value in capital budgeting further leads to a lower construct accessibility of a possible project abandonment in managers, thereby leading to a higher level of escalation of commitment (Denison, 2009). 2.4.3 real options The term of real options was introduced by Myers (1977) and defined as real options are growth opportunities for a firm whose value depends on the firm’s future investments. This would divide the value of a firm into the value of the firm’s assets and the value of the firm’s growth options (Collan and Kinnunen, 2009). RO determines firm value by taking into account the variety of possible management options (managerial flexibility) in an investment opportunity. The RO valuation incorporates options such as expansion or abandonment of the investment in the calculated value, where the highest of the possible values is chosen. Denison (2009) explains, “The use of real options in capital budgeting basically involves considering possible decision points that could arise as a project unfolds and the best response of management at each of these decision points. The value of the project should management choose the best option at each of these points is calculated, and a weighted average of these possible outcomes is taken based on their probability of occurrence”. A potential shortfall in RO is the level of sophistication the model requires. Complicated mathematical models intimidate managers whose choice is to instead use simplistic capital budgeting models that they feel comfortable using and interpreting (Lander and Pinches, 1998). Additionally the assumptions required for performing RO modeling are often violated in practice (Lander and Pinches, 1998). 2.5 hyPOThESIS Accessibility of cognitive constructs, such as personality traits, attitudes and choice options, is defined by psychology as the ease with which these constructs can be brought to mind (Higgins, 1996). The construct accessibility can be increased through repetition (Higgins and King, 1981) or through task instructions (Higgins and Chaires, 1980) By failing to incorporate RO in the decision phase, executive management ignores the value of managerial flexibility of early project termination. However managers that do incorporate RO models in their capital budgeting, will repeatedly be exposed to the option of early abandonment in contrast to managers that only use NPV or PB. This will result in RO users having an increased construct accessibility of early project abandonment due to the construct of early project termination being activated more frequently through written instructions in RO participants compared to NPV or PB participants (Higgins et al, 1982).
Review of Business and Economics Studies Volume 2, Number 3, 2014 Additionally Posavac et al(1997) states that when decision alternatives are salient, the decision-maker will be more likely to choose the preferred alternative. However, if the decision alternatives are left unspecified, the decision-maker will have to access the construct from memory, which potentially leads to a complete negligence of the preferred alternative. The negligence of the preferred alternative occurs according to Posavac (1997) when the accessibility is insufficient to retrieve the preferred alternative from memory. Since the preferred alternative in this experiment is early project abandonment, decision-makers using the capital budgeting method RO, which has task instructions and salient decision alternatives about early project abandonment, should display a lower level of escalation of commitment compared to decisionmakers using NPV or PB. Hypothesis 1: Project abandonment decisions in the case of unprofitable projects will be more probable when Real options are used explicitly for project decision-making compared to solely using Payback or Net present value. Hypothesis 2: Project abandonment decisions should not vary between capital budgeting methods Payback and Net present value, which do not take into account early project abandonment value in their calculations. 3. METhODOlOGy The experiment was a quantitative study conducted through an online survey. In order to constrain unauthorized people from having access to the experiment, the survey was only accessible to selected participants at Gothenburg School of Business, Economics, and Law chosen prior to the experiment. A potential shortfall of the experiment is the simplified experimental setting used, distant from capital budgeting situations in reality. This should not have an effect on the results, as there is a close similarity between experimental surveys and realistic field studies in research on organizational behavior (Locke, 1986). Additionally Griffin and Kacmar (1991) argue that experimental surveys provide a valid and useful approach in many situations. 3.1 Participants The participants consisted of 293 past and current MSc Finance, MSc Economics, and Bachelor students with Corporate Finance major from University of Gothenburg School of Business, Economics, and Law in Gothenburg, Sweden. The distribution of participants was 147 Corporate Finance students (50.17%), 107 Finance students (36.52%) and 39 Economics students (13.31%). The participants were chosen because of their theoretical knowledge of the capital budgeting methods used in the experiment. Use of students as subjects is consistent with the recommendations in Gordon et al(1987) and is justified by the findings of Ashton and Kramer (1980) displaying similar results with students and nonstudents in decision-making studies. A total of 48 students completed the experiment, yielding a 16.38% response rate and were divided accordingly among each capital budgeting method: 16 NPV responses, 15 RO responses, and 17 PB responses. The average age of the 48 participants completing the experiment was 23.46 years and 39.58% were female. 3.2 CASE GIvEN TO PArTICIPANTS, APPENDIx B The case provided to each participant regarded a development of a new cell phone hard drive. This new hard drive had a higher storage capacity while maintaining production costs and dimensions constant compared to current cell phone hard drives. Each of the participants played the role of a controller for Ericsson AB who was responsible for project evaluations, and was given an example with calculations of how to use their assigned capital budgeting method. The example provided was given to the participants to guarantee an understanding on how to solve the case, and the participants could at any time refer back to the example while performing their own calculations. Furthermore the participants received information about the forecasted cash flows, project lifetime, probability of success/failure and abandonment value of the Ericsson cell phone HDD project. PB participants received exclusive information about a historical average accepted payback period of 3 years for past projects undertaken by Ericsson to use as a reference point in their investment recommendations. Performing the calculations correctly for the Ericsson Cell Phone HDD project, NPV and RO calculations yielded values of positive $26,000,149.51 and $29,091,031.42 respectively, while PB yielded a payback period of 2.27 years. Correct calculations by the participants should therefore unambiguously lead to funding the project regardless of capital budgeting method used. After performing the initial project evaluation, additional information explaining a project setback was presented to all case participants. The setback was due to an unexpected competitor entering the market with a superior product. All participants received information about current level of project completion, sunk costs and modified forecasted cash flows based on new demand. Forecasted cash flows became
Review of Business and Economics Studies Volume 2, Number 3, 2014 definite after the project setback and the calculations for NPV and RO yielded the same positive project value of $42,272,795.23, while the payback period for the project increased to 5 years. Simultaneously Ericsson AB could sell the project for 65% of invested capital, thereby yielding an abandonment value of $55,250,000, being $12,977,204.77 higher compared to the calculated NPV and RO value. Correct calculations would indicate an abandonment being more profitable compared to a project continuation, which therefore should lead to an unambiguous choice of project abandonment in NPV and RO participants. The calculated payback period would exceed the average accepted payback period of 3 years, and, correspondingly to NPV and RO, should lead to project abandonment. 3.3 PrOCEDurE FOr CASE STuDy The participants were randomly assigned one of the three capital budgeting methods (RO, NPV and PB), and contacted by email inviting them to participate in the experiment. In the email, participants were asked to take part in an experiment by solving a case study explicitly using the assigned capital budgeting method. After having read the Ericsson Cell Phone HDD case, each participant was asked to value the project by using the appropriate capital budgeting method. Based on the project value each participant provided a recommendation of whether to fund the project or not on a 10-point scale (1 not likely at all and 10 extremely likely) and a short motivation (1–2 sentences) defending their choice. Because of the apparent decision to accept the project, recommendations below 5 indicated a lack of understanding of the capital budgeting method used or incorrect calculations. 2 participants using RO calculations (4.17% of total, 13.33% of total RO participants) answered with recommendation values below 5, and therefore their values were excluded from the future analysis. After the initial recommendation the participants were informed about a setback in the project. They were asked to revalue the project by using the same capital budgeting method as for their initial valuation, and provide a recommendation whether to continue the project or not on a 10-point scale (1 not likely at all and 10 extremely likely) and a short motivation (1–2 sentences) defending their choice. 3.4 MANIPulATION ChECK AND DEMOGrAPhIC quESTIONS Following the project valuation and investment recommendations participants were asked to answer a series of manipulation check questions and state ments. The answers were measured on a 10-point scale with 1 being “Strongly disagree” and 10 being “Strongly agree”. The questions were “To what extent do you agree that the firm uses the given capital budgeting method to evaluate its investment decision?”, “I considered the possibility that the cell phone HDD project could fail before making my recommendation about whether to undertake the project”, “I considered the possibility that the cell phone HDD project could fail before making my recommendation as to whether to continue developing the project”, “The case was difficult to do”, and “The case was very realistic” defining variables Eval, PFail1, PFail2, Diff and Rea respectively. Following the manipulation check questions, all participants were asked the same demographic questions to determine the focus of study, previous work experience, age, gender and theoretical knowledge and practical usage of the three capital budgeting methods. 3.5 STATISTICS The experiment was a repeated measure design where participants were assumed to be the same across the three capital budgeting methods. The betweensubjects variable was the capital budgeting method (CapBud), which was manipulated at three levels (RO, NPV, PB). The within-subjects variable, time of recommendation (Time), was manipulated at two levels (Time1 and Time2). CapBud, the first independent variable, was manipulated at three levels. Participants were randomly assigned to one of the three capital budgeting methods used and asked to explicitly use the assigned method (PB, NPV, or RO) in their investment calculations. The second independent variable, Time, was manipulated at 2 levels. Participants were asked to provide investment recommendations at two points in time, the first being the initial investment decision (Time 1) and the second deciding whether to continue the project after the setback or not (Time 2). The dependent variable to test both hypotheses is the recommendation to continue the project (RCP) and is measured at two different times. At Time 1, RCP was measured to validate knowledge of the participants and to eliminate potential outliners skewing the results, and at Time 2 measuring the degree of escalation of commitment. A higher RCP score at Time 2 would indicate a higher degree of escalation of commitment due to opposition of project abandonment by the participant. The most common method of measuring escalation of commitment is in monetary commitment. In this experiment, similarly to Kadous and Sedor (2004)
Review of Business and Economics Studies Volume 2, Number 3, 2014 and Denison (2009), escalation of commitment is measured on a scale indicating the likelihood of recommending a project continuation. 3.6 BIAS AND OThEr DATA ISSuES Due to a low response rate two tests were run to investigate possible non-response bias. To do this an additional email was sent out to all participants asking those that did not participate in the case to answer two questions. The questions established age and determined knowledge in the three capital budgeting methods RO, NPV and PB. Assuming only participants not having done the case study replied to the email a total of 86 (29.35% of total number of participants) new replies were recorded. The answers from both groups (those having done the case and those that did not do the case) were statistically compared to each other to determine if the sample was a good representation of the population. The questions to establish age and determine knowledge in the capital budgeting methods used were the same for both groups. No difference was recorded between the knowledge in NPV and PB since all participants (100% of those that did the case and those that did not do the case) answered they were familiar with the two capital budgeting methods. A statistical comparison was therefore only made for age and familiarity with RO. The answers from the follow-up email defined two variables: The variable RO was as a dummy variable measuring if they had previous knowledge about RO (1 had knowledge or 0 did not have knowledge) and Age measuring the age of the respondents. The two variables were compared between groups (those having done the case and those that did not do the case) to test if the sample of students having done the case was a good representation of the population. The results showed that both tests were not significantly different from each other and therefore indicated that the sample was a good representation of the population (RO p=0.721 and Age p=0.422). 4. EMPIrICAl rESulTS 4.1 MANIPulATION ChECK quESTIONS 4.1.1 Manipulation check questions results The results in Table 1 show the mean value for each of the manipulation check questions and Table 2 shows the significance between the different capital budgeting methods for each question. The manipulation check questions displayed significant differences in three out of five questions (see Table 2). Variables Diff (p=0.168) and Rea (p=0.454) measuring: How dif ficult the case was, and How realistic the case was, were between the capital budgeting methods not significantly different from each other (see Table 2). The p-value for variable Diff and Rea indicates that the participants found the case of equal difficulty and equally realistic, independent of capital budgeting method assigned. Variables Eval, PFail1, and PFail2, measuring the evaluation of capital budgeting method used and awareness of project failure at Time1 and Time2, each had a significance of p<0.05, thereby indicating a difference between the three capital budgeting methods (see Table 2). Since a rejection of the null hypothesis (H0: m1=m2=m3, where m1= Mean of RO, m2= Mean of NPV and m3= Mean of PB) in Table 2 only indicates a significant difference between three variables, but not between which variables, a post hoc test is required to determine which variables are significantly different from the rest. A post hoc Bonferroni test was used to identify which capital budgeting method (s) the significance derived from (see Table 6 Appendix A) Table 6 indicates that RO (p=0,00) and NPV (p=0,042) were considered as significantly better capital budgeting methods compared to PB for project evaluation. Regarding variable PFail1 the participants demonstrated a higher awareness of project failure in their initial calculations by using RO compared to NPV (p=0,00) and PB (p=0,00). For PFail2, awareness of project failure after the setback was again significantly higher in participants using RO compared to NPV (p=0,00) and PB (p=0,00), but also between NPV and PB (p=0,008). 4.1.2 Manipulation check questions analysis A significant difference in variable Eval was anticipated. This can be explained through academia arguing Table 1. Mean values for Manipulation check questions. Mean rO NPv PB Eval 9.46 7.94 6.06 PFail1 9.15 6.06 5.00 PFail2 8.85 6.19 4.53 Diff 2.62 1.88 2.71 rea 7.69 7.06 7.71 Mean value of manipulation check questions on a 10-point scale labeled (1 “Not likely at all” and 10 “Extremely likely”) for capital budgeting methods RO, NPV and PB. Definition of variables: Eval “Evaluation of capital budgeting method”, PFail1 “Awareness of project failure at Time 1”, PFail2 “Awareness of project failure at Time 2”, Diff “Difficulty of the case” and Rea “Realism of the case”.