The Escalation of Commitment Among Business Angels
Antecedents and consequences of escalation in business angel investingDanny Groothuis 1920979
MSc Small Business and Entrepreneurship RijksUniversiteit Groningen
Abstract:
This empirical research examines the antecedents and consequences of escalation of commitment in a quantitative manner on a business angel dataset. While the current literature already provides rich research on the determinants of escalation of commitment, the concept has not been tested in a business angel context so far. Furthermore the outcomes as a consequence of this escalation behavior prove to be an under researched field. In order to increase the comprehension of not only this distinguishing investment group but also this very concept, hypotheses derived from existing literature are generated to test these antecedents and possible consequences. A dataset of 1,137 business angel investment exits is utilized for statistically providing proof to either accept or reject these hypotheses. These results suggest that management and industry experience, the degree of personal responsibility, the amount of hours due diligence and investments in the seed and start-‐up stages are the determinants that significantly influence escalation of commitment among business angels. At the consequences side of the equation the termination of a failing course of action leads to negative consequences, however when this failing course of action is persisted more favorable outcomes occur.
Introduction
Current knowledge teaches us that entrepreneurs have a significant influence on the formation of new firms. The fact that their entrepreneurial ventures are the main generators of new jobs and should be held accountable for the introduction and commercialization of new products has been proven extensively in a vast amount of studies (Birch 1979; Davidsson, Linmark & Olofsson., 1994; Storey, 1994;). However nowadays these ventures and their owners experience several issues obstructing their growing abilities. Over the past decade entrepreneurs and early stage firms around the globe report increasing difficulties with not only attaining finance, but also finding skilled staff and experienced managers (Binks, 1996; Mason & Harrison, 2000; Sørheim, 2005).
According to the European Commission (2014) SMEs from various member states report problems with the accessibility of finance (32%) and the availability of skilled staff and experienced managers (24%). To make matters worse not only banks but also equity investors are shifting their focus to investing in the more mature stages of the company. This leaves the entrepreneur without the necessary financial assets to grow their ventures into organizations that are able to positively contribute to the economy.
Fortunately there is still one group of investors that is able to tackle both of the relevant issues reported by the European Commission; business angels. These are wealthy individuals that invest a percentage of their personal wealth preferably into early stage ventures. Additionally business angels take an active role in the company and contribute through their accumulated experience and knowledge gathered during their life. Due to their unique investment characteristics and active approach vis-‐à-‐vis the reported problems among SMEs it is therefore important for governments and policy makers to ensure that business angel assistance will be allocated as efficient as possible (Aernoudt, 2005; Politis, 2008).
and expensive errors for decision makers in resource allocation decisions (Brockner, 1992). A habit of “throwing good money after bad” is revealed within various research disciplines such as economics (Berg, Dickhaut & Kanodia, 2009), marketing (Schmidt & Calantone, 2002) and finance (Schulz & Cheng, 2002). Aptly termed the escalation of commitment (Sleesman, Conlon, McNamara & Miles, 2012; Staw, 1976), such behavior seems to be highly applicable to business angel investors.
Among the primary investment motivations of these investors we find both generating a return on investment and facing the challenge of succeeding in a new project (Aernoudt, 1999). Research confirms escalation of commitment to be highly relevant in investment situations that include vast initial investments of resources such as time and money (Staw, 1976). Therefore business angels are expected to be prone to the escalation of commitment. Moreover varying other factors exposed by escalation research are applicable to business angels such as personal responsibility for the initial decision to invest (Staw, 1976), the amount of sunk costs (Arkes & Blumer, 1985) and the decision-‐maker’s experience and knowledge (Jeffrey, 1992).
Sticking to such an initially wrong decision could be regretful for these very investors. Not only because resources were allocated in vain, but also since their knowledge would have been put to better use in an other investment. Opposing to these negative consequences, the outcome can in fact also be positive. A business angel continuing an investment due to the determination to make the company succeed exemplifies this. Situations where simply pulling the plug seems logical can have detrimental effects such as forcing the business cease its operations.
improve our understanding of this escalating phenomenon in a broader context, but also can notify business angels in recognizing its determinants and be conscious of the outcomes. Ultimately the results can support in practical conditions by decreasing the amount of inefficiently allocated resources through establishing awareness of the antecedents and consequences.
This paper contributes to the existing literature by quantitatively testing logically derived hypotheses from the existing escalation of commitment research in a business angel context. Its objective is to answer the research questions ‘which determinants form the antecedents for escalation behavior in business angel investments?’ and ‘what are the consequences of escalation behavior for the outcomes of business angel investments?’ The determinants under investigation are selected from the existing studies on the factors leading to the escalation of commitment.
To be more precise the influence of project, psychological and social
determinants leading to escalation behavior will be tested. At the other end of
the equation, the effect of escalation behavior on possible outcomes is tested in order to answer the corresponding research question. This will increase our comprehension of the outcomes of escalation of commitment. Specifically, on either positive or negative consequences for the business angel investor and the firm invested in. Both the determinants and outcomes are tested on a dataset containing 1,137 business angel investments between 1990 and 2007. From the resulting output conclusions are drawn in order to answer the stated research questions.
This paper is structured as follows. Initially this document will provide a literature review on the business angel and escalation of commitment literature. Subsequently it outlines the methodology for this research including dataset characteristics and research methods applied followed by the results obtained from the investigation. Finally this paper will end up in a discussion based on these findings, including the limitations of the investigation and suggestions for future research.
Literature review
Business Angels
Within the venture capital market there are two groups that can provide early-‐stage financing for entrepreneurial firms: venture capitalists and business angels. Regular financial institutions such as banks are incrementally hedging their risk by investing in established companies in their growth stages. This leaves entrepreneurs with increasing difficulties to attain finance (van Osnabrugge, 2000). Their inability to attain a loan or if so, against abnormal rates) is due to their inherently uncertain and high-‐risk nature. Logically this forces entrepreneurs and their firms in the seed and start-‐up stage to find their salvation on the venture capital market (Wetzel & Freear, 1996).
Both type of investors, venture capitalists and business angels, aim at generating positive returns by investing in high potential SMEs that will compensate for the risks involved (van Osnabrugge, 2000). Furthermore these investors can provide a signaling function towards banks for future finance (Sørheim, 2005). Venture capitalists, who are regarded as intermediaries between financial organizations (e.g. pensions funds, insurance companies, etc. (Mason & Harrison, 1999)) and unquoted firms, gather finance from these institutions to invest in promising companies (Lumme, Mason & Suomi, 1998). These capitalists are professionals who tend to focus on long-‐term equity finance in more mature firms. Here the primary reward is eventual capital gain without directly interfering with the management of the firm (Sapienza et al. 1996). Whereas there are numerous dissimilarities between business angel investors and venture capitalists, the differences that are noteworthy are found in table 1.
Table&1&Main&differences&between&business&angels&and&venture&capitalists
Main&differences Business&angels Venture&capitalists
Personal Entrepreneurs Professional&investors
Firm&experience Small,&earlyAstage Large,&mature
Source&of&finance Own&capital Market/other
Due&diligence Lower Extensive
Location&of&investment Of&concern Not&important
Contract&used Incomplete/simple&contracts Full/comprehensive&contract
Monitoring&after&investment Active,&handsAon Strategic
The most important two differences will be explicitly discussed in order to illustrate the distinctive features of a business angel.
First of all it is essential to highlight two distinguishing features of business angel support in comparison with regular venture capital. The first feature is the hands-‐on mentality with regard to managing the company (Avdeitchikova, Landstrom & Mansson, 2008). With the expertise gathered from previous occupations it is not only the financial capital that business angels provide. Also commercial skills, entrepreneurial and management experience, business knowledge and network contacts can help make a difference in the entrepreneurial phase of the firm. Therefore is business angel support inventively termed as ‘intelligent money’ (Avdeitchikova et al. 2008; Ehrlich, De Noble, Moore & Weaver, 1994; Mason & Harrison, 1995).
Additionally there is the application of the principal-‐agent problem. For venture capitalists this implies situations where there is a complex construction of the fund manager being both a principal and an agent (principal towards the entrepreneur and agent for venture capital fund providers) (van Osnabrugge, 2000). Such a complex construction can lead to settings where the interest and goals of the agent diverge from those of the principal. Van Osnabrugge (2000) also provides an additional explanation for the reduced possibility of this issue occurring among business angels. It is the fact business angels prefer to work according to the incomplete contracts approach instead of a principal-‐agent approach that is favored by venture capitalist. This incomplete contracts approach inherits that due to the active involvement in the investment business angels do not need strict contracts since these will always be incomplete. It is the ex post allocation of control that aligns the interests of both the angel and the firm owner. Opposing to this venture capitalist will implement contracts in order control the agent’s efforts in combination with observation and enforcement mechanisms for reinforcement However these differences seem crystal clear, finding an exact definition for the concept business angel itself can be problematic.
“A high net worth individual, acting alone or in a formal or
informal syndicate, who invests his or her own money directly in unquoted companies in which they have no family connection and who, after making the investment, generally takes an active involvement in the business, for example, as an advisor or member of the board of directors“ (p.309).
Additionally from a wide arrange of different studies on business angels a common profile can be drawn. The typical business angel is a “middle aged male
who invests a relatively large amount of his personal wealth, most often in young and technology-‐oriented firms” (Aernoudt, 1999; Mason, Harrison & Chaloner,
1991; Politis, 2008; Reitan & Sørheim 2000)
Also investigation points out that a significant majority possesses previous start-‐up experience such as 96% in Sweden (Landstrom, 1993), around 85% in Finland (Politis, 2008) and 83% in the US (Gaston, 1989). Overall it can be stated from research in a wide range of geographical locations and contexts that a large majority of business angels seem to have the experience to manage and harvest a successful entrepreneurial firm (Aernoudt, 1999; van Osnabrugge, 1998; Wright & Robbie, 1998). According to Politis (2008) it seems reasonable to assume that this background provides the knowledge to conduct the prior due diligence needed before considering to commit to the investment. Their acquired business know-‐how helps to evaluate the benefits and risks associated with the prospective informal investment (Politis & Landstrom, 2002).
Eventually goal of the business angel is, next to leaving behind a viable and prosperous company, to realize a favorable return on the amount invested. Whereas commitment can be seen as an important driver of such success, the threat of overcommitting is always present. Therefore it is important to be aware of escalation behavior, also termed as escalation of commitment.
Escalation of Commitment
The very first research paper revealing escalation behavior to exist was written by Staw (1976). Within his research, he already experimented with the concept in an investment context. Subjected to his research 240 business school students performed in a role-‐playing exercise where “personal responsibility and decision consequences were the manipulated independent variables”. The results indicate that participants who are personally responsible for negative consequences on an initial investment commit the greatest amount of resources to this previously chosen course of action.
In his following paper Staw (1981) argued that at least some of the tendency to escalate commitment is explained by self-‐justification motives. This self-‐justification approach claims “decision makers become entrapped in a previous course of action because of their unwillingness to admit – to themselves and/or others – that the prior resources were allocated in vain” (Brockner, 1992, p. 39).
While the self-‐justification theory remains the dominant explanation for escalation tendencies, additional literature streams emerged to either complement or replace it. The most popular one is the partial explanation by the expectancy theory. This theory proposes that decision makers take into account certain prospects such as the value of attaining the goal and the probability to succeed in attaining this goal when assigning additional resources to an already chosen course of action (Brockner, 1992; Savage, 1954).
Tversky and Kahneman’s ‘prospect theory’ (1979) is a theory that fits the occurrence of escalation of commitment from a subjective expected utility theory point of view. Prospect theory predicts that the risk-‐taking propensity of individuals is influenced under conditions of risk and uncertainty. It starts out with a reference point (e.g. initial amount invested) and situations that are negative as regard to this point will induce decision makers to take more risk. Vice versa in situations positive of this reference point the decision maker is risk-‐averse. To conclude, losses are associated with risk-‐taking propensity and profitable positions with risk-‐reducing behavior. Prospect theorists therefore assume that the escalation of commitment is commonly found in the sphere of losses (Brockner, 1992).
A final theoretical lens that can be applied to explain escalation situations is the agency theory. This theory suggests that principal-‐agent problem can come into existence in particular investment situations. Especially in those where the incentives for the decision-‐maker conflict with the interest of the investor. To be precise, when agency situations occur decision makers may act in a self-‐ interested way and escalate at the expense of the principal (Booth & Schulz, 2004). By aligning managerial incentives with the goal of the investor (e.g. through detailed contracts) the negative pathway of escalation is blocked, forcing it into a positive direction for the principal (Sleesman et al. 2012).
As a concluding remark it is important to indicate that escalation behavior does not necessarily leads to negative outcomes. There is a sufficient amount of situations where the escalation of commitment will lead to successful outcomes, or in other words where persistence is rewarded. A perfect example is the traditional leadership trait of goal determination. Where determined decision-‐ makers are deemed more credible by sticking with their decision instead of continuously altering the course of action (Staw, 1976). This also indicates that a subjectively positive outcome (e.g. self-‐justification) can be enforced. The motivation for attaining such positive results is also explained by escalation theories. However what is determining this escalation behavior in the first place?
The Antecedents of Escalation of Commitment
In a follow up on their initial research, Staw and Ross (1987) indicate that four distinguishable categories are regarded as the determinants that influence the escalation of commitment. The meta-‐analytical review on the determinants of escalation behavior by Sleesman et al. (2012) verified these domains and investigated the corresponding theories applied explaining these determinants. With the assistance of this review the following can be said about the
psychological, structural, social and project-‐related determinants:
Project determinants include the details concerning the initiation of the
course of action in the first place such as the information available (and related uncertainty) and the positive performance trend before taking the root decision (Moon and Conlon, 2002). The dominant theory in this realm is that of expected utility since individuals will make the decision to either keep escalating or terminating the course of action depending on which option is leading to the highest utility.
Psychological determinants include factors such as sunk costs and time
invested prior to taking the original decision (Arkes & Blumer, 1985; Soman, 2001), personal responsibility for taking the initial decision (Staw, 1976) and the reputational damage of cutting the current course of action in terms face-‐saving and determination (Zhang & Baumeister, 2006). In short all determinants regarding the cognitive and affective information processes executed by the individual making the decision to escalate or not (Brockner, 1992). In this area the self-‐justification theory stream dominates prospect theory related explanations.
Conclusively there is the, in comparison, under-‐researched part of
structural determinants that can be defined as “the structural features of an
organization and its interaction patterns” (Staw and Ross, 1987). This includes contextual elements and organizational features of the organization taken into account in escalation dilemmas (Bowen, 1987). These determinants are mainly the domain of principal-‐agent theories and apply to situations where the principal-‐agent problem is at hand. Sleesman et al. (2012) conclude that this determinant is under-‐researched in comparison to the others. Yet the possible outcome(s) of escalation to commitment appear to be an even more under explored domain in this research stream.
The Consequences of Escalation of Commitment
While some papers that laid the foundation for escalation research focus on the escalation towards a failing course of action (Brockner, 1992), others seem to be neutral about this course (Staw, 1981). However the majority of papers has a focus on this course of action as subject instead of the actual outcome of such behavior. The cause of this complication lends itself to various explanation.
First of all the outcomes of escalation behavior seem to be very context-‐ specific and depending on the theoretical lens applied. To elaborate on this matter, the eventual outcome resulting from the escalation behavior is mainly based on personal motivation to persist with the current course of action (Brockner, 1992). Since many of the introduced theories suggest that these motivations are subjective (e.g. self-‐justification), it can be hard to determine whether or not the consequence of escalation is positive or not. In short, the outcome of escalation behavior is in the eye of its beholder. As an example in the light of the self-‐presentation theory (Grant & Mayer, 2009), the chosen course of action can eventually be forced into a positive outcome through escalation. This is highly relevant for the manager or investor when the favored outcome is to be seen as competent.
From an agency perspective the multi interpretability of the outcome is
agent can be specified as negative for the principal (van Osnabrugge, 2000). Though highly subjective to the principal-‐agent problem, the majority of all research however, is done in either investment or management situations (Sleesman et al. 2012). However when actively participating in an investment the incomplete contracts approach suggests that the goals will be more aligned due to the post-‐investment allocation of control. This reduces agency costs and can force escalation behavior to inherit positive outcomes for the both the investor and the firm invested in (van Osnabrugge, 2000).
Hypotheses
In this research various assumptions from the majority of the determinant types relating to certain aspects of the escalation of commitment are tested. Unfortunately due the nature of the dataset (see research design section) the variables falling under one the final determinant are not included. This restricts us from investigating the structural determinants.
However these are also not as relevant for business angel investments since these determinants are more applicable to contracting situations such as venture capital investments. Mainly due to the incomplete contracts approach (van Osnabrugge, 2010) involving the ex post allocation of control increases the aligning of business angel and company goals.
In its turn the outcome side also consists out of two variables. These are manipulated by the previously stated escalation variables to test how escalation influences the objective outcome. First the financial outcome of the investment, after exiting, is taken as a consequence of escalation. Second the possibility of escalation leading to the firm invested in ceasing its operations. At the outcome side the hypothesis are stated according to those theories that seem fit to explain the consequence of escalation.
Antecedents
Social determinants.
The first set of hypotheses is found in the realm of social determinants. This area of determinants has its foundations for the majority in the self-‐ presentation theory. Therefore business angels deem it important to be seen as competent manager or entrepreneur.
The competency of a business angel, measured in years of experience on specified aspects such as management, industry and entrepreneurial experience, can have a substantial influence on performance (Wiltbank et al. 2009). Especially the amount of experience should play a role in the probability of escalating commitment due to the fear to be labeled as incompetent. Individuals that posses high management experience will rate themselves as competent managers that are able to run a company and have the ability to motivate people. These skills are required to attain positive results and can thus lead to a successful investment. As a result of the self-‐presentation theory, in situations where a company is not performing according to the prognosis, high levels of management proficiency will lead to escalation behavior in order to prove that these results are not the outcome of incorrect management. Thus leading to the hypotheses;
1a Business angel investments including more management experience will demonstrate a higher total reinvestment amount.
1b Business angel investments including more management experience will also result in a longer period the investment is held.
More or less the same can be stated for entrepreneurial experience.
Especially for seed and start-‐up ventures it is important to have entrepreneurial experience. This type of experience can make the difference in for example the development and commercialization of new technologies in the correct way and attaining further finance. Entrepreneurial competency for business angels can therefore be crucial to establish a profitable venture that can contribute to a successful investment exit. However, again it is logical to assume that business angels with entrepreneurial experience are afraid to be seen as incompetent according to the self-‐presentation theory. This leads to exhibiting signs of escalating behavior when the enterprise is not performing as expected, inducing the following hypotheses:
2a Business angel investments including more entrepreneurial experience will demonstrate a higher total reinvestment amount.
2b Business angel investments including more entrepreneurial experience will also result in a longer period the investment is held.
The final type of experience that will be investigated is the knowledge of the industry or industry experience. In line with the previous types of experience it can be stated that underperforming in an industry related to the accumulated industry experience of the business angel will resort to face-‐saving actions. Again the assumption is that competency, in this case industry experience, will be positively related to signs of escalating behavior:
3a Business angel investments including more industry experience will demonstrate a higher total reinvestment amount.
3b Business angel investments including more industry experience will also result in a longer period the investment is held.
Psychological determinants.
In this area the cognitive and affective information processes of the business angel investor are the cause of escalation. This includes factors such as personal responsibility and the amount of resources utilized before making an initial investment. As Staw (1972) proved in his early experiments, being personally responsible for the investment will increase the probability of the escalation of commitment. On the other hand the meta-‐analysis by Sleesman et al. concluded that “the sharing of decision authority may lead to higher levels of commitment” (2012, p. 557) These differing outcomes will be retested in a business angel context to demonstrate the connection of individual responsibility to escalation behavior. Backed by the self-‐justification theory, it is expected that business angels will decrease commitment at the moment the amount of investors increase. The lower personal responsibility for the initial decision to invest diminishes the motive to self-‐justify, thus leading to lower escalation effects. Arriving at the induction of the following hypotheses;
4a Business angel investments including a higher number of co-‐investors will demonstrate a lower total reinvestment amount.
4b Business angel investments including a higher number of co-‐investors will also demonstrate a shorter period the investment is held.
Another determinant in this area is the amount of resources committed prior to making the initial investment decision. For business angels this main pre-‐ investment resource is time. The amount of hours spent on due diligence will increase the angel’s certainty of making the correct investment decision. When this investment is not performing as expected the time of due diligence will influence the business angel to stick with the decision. From the self-‐justification perspective the business angel will justify his initial decision through increasing commitment when the amount of time invested on due diligence is under threat of being in vain. Summarized into hypotheses:
5a Business angel investments including higher amounts of due diligence will demonstrate a higher total reinvestment amount.
5b Business angel investments including higher amounts of due diligence will also demonstrate a longer period the investment is held
Project determinants.
Including the details concerning the initiation of the course of action, project determinants are another source leading to the escalation of commitment. Whilst being a distinctive feature of investing in the early stages of an enterprise, business angels will increase escalation behavior through this decision. At these stages the firm does not have a performance track record and are thus accompanied with a marginal amount of information and insecurity/uncertainty (Bowen, 1987). Since the company has not yet attained phases of growth the decision to invest is based upon expected performance and should be regarded as a mere educated guess. Reinforced by the expected utility theory business angels will therefore inherit signs of escalation behavior when the investment is made in the seed and start-‐up stages of the firm in order to attain a successful outcome due to the uncertainty involved. The hypotheses related to this determinant are therefore:
6a Business angel investments in the early stages of a firm will demonstrate a higher total reinvestment amount
6b Business angel investments in the early stages of a firm will demonstrate a longer period the investment is held.
Consequences.
in vain and, based on this belief, escalation behavior can therefore result into a negative investment outcome.
However, according to the prospect theory by Tversky and Kahneman (1979) business angels will increase their reinvestment amounts in the domain of losses related to the reference point (0 profit). By doing so it the investor aims at reattaining or even exceeding this initial reference point. The ultimate goal is therefore to either profit from the investment, or in the worst case to break-‐ even. Based on these assumptions it can be theorized that after initially demonstrating the case of ‘throwing good money after bad’ associated with negative investment outcomes, eventually sacrificing a sufficient amount of resources (both financial and in terms of time) will lead to a positive outcome for the investment as regard to the reference point.
7a Business angel investments including higher total reinvestment amounts will at first demonstrate losses, but eventually result in a more positive investment outcome.
7b Business angel investments including higher amounts of years the investment is held will at first demonstrate losses, but eventually result in more positive investment outcome.
8a Business angel investments including higher total investment amounts have a lower probability of resulting into the firm ceasing its operations
8b Business angel investments including higher amounts of years the investment is held also have a lower probability of resulting into the firm ceasing its operations.
Research design
Dataset
In order to test the generated hypotheses a database that consists out of 1,137 business angel investment exits is utilized. This data is gathered by the Kauffman foundation through the ‘Angel Investor Performance Project’ (AIPP) among 539 angel investors. This population of angel investors operated in the geographical region of North America between 1990 and 2007. The focus for gathering this data by the AIPP was mainly on the pre-‐ and post-‐investment strategies through surveying the details of the entry and exit of a specific investment (Kauffmann, 2015).
However the data also includes variables related to the business angel investor, the investment itself and the company invested in. For the business angel this data not only comprises out of variables specifying the initial amount invested and follow-‐up investments but also pre-‐investment experience, the amount of co-‐investors and hours devoted to due diligence before investing. Data collected on the termination of the investment contain total profits/losses and the years of investment, reinvestment and termination are also included as investment related variables. Also on a firm level the dataset includes indicators for the strategy applied by the company (e.g. focus on attaining cash flow), the industry the firm is operating in and the result of the investment exit for the organization (e.g. the firm ceased operations). Regrettably no fundamental firm-‐ related variables such as firm age and size are gathered in this set.
At the downside of using this existing dataset there is the fact that the crucial data for investigating escalation of commitment is incomplete for the majority of respondents. Especially the variables such as (re)investment amounts, the business angels’ personal characteristics (e.g. experience) and company specifics hamper with this issue. This leads to a drastically lower amount of investments suited for the research as compared to the full dataset. As indicated there is also no data on the features of the organization’s features and contextual elements, this obstructs the possibility to test the effect of the structural determinants.
Furthermore it is important to point out that all values were self-‐reported by the business angels that were surveyed. Even though reported anonymously this can lead to biased values for factors such as the amount (re)invested, the amount of experience possessed and optimistic outcomes of the investment. Conclusively, the database is an outcome from surveys conducted with another purpose in mind and therefore not exactly measuring the escalation of commitment concept. As a logical consequence the methodology for the variable testing approach needs to be tailored towards the dataset in order to retain required information.
Research Methodology
Antecedents
investments comprising out of investments in either the seed or start-‐up stages of the firm.
Escalation of Commitment Variables
In the domain of the dependent variables that are manipulated by the hypothesized determinants we find two escalation of commitment concepts. First of all the effect of the antecedents on the total amount reinvested is measured, this reinvested amount is the total amount of money in $ invested after the initial investment. As a consequence of the incomplete nature of the data the exact reinvestment amounts are not included for the majority of investments. Therefore it is not possible to investigate incremental investment amounts as stated by the prospect theory (Tversky & Kahneman, 1979). This results in a dependent, continuous variable measured as the total amount invested minus the initial investment to approximate escalation of commitment in financial resources. The independent determinants will be tested through linear regression in both a single effects model where the input consists out of one variable (plus control variables) at a time and a full model where all determinants are included. Outcomes from this model imply whether or not hypothesis 1a to 6a can be accepted.
Additionally the effect of the antecedents of the escalation of commitment concept will be measured in the total length of the commitment in years invested as an alternative resource. Sensibly this is measured through the difference between the year of initial investment and the year of exit. The outcome is also a dependent, continuous variable that is tested in a linear regression model. Again the various independent variables will be individually tested for their significance in contribution to the length of the investment and similarly tested in a complete model involving all independent variables. The decision to accept hypothesis 1b to 6b is based on the results gathered from this model.
Consequence Variables
independent factors. The outcome of the business angel investment is tested on two levels: the consequence for the business angel and for the firm. Initially the result for the business angel is measured in financial terms for hypothesis 7a and 7b. By subtracting the total amount invested from the investment return a continuous performance variable is retained. Both escalation of commitment types (in terms of time and money) will be tested on linear regression with the investment outcome in individual effects and complete effects models. In addition a curve linear estimation is executed to test for quadratic regression for possible convexity in the regression function.
Consecutively the consequence for the business itself is inspected. A
categorical variable that specifies the type of exit from the investment is utilized for this (comprising out of ceased operations, shares bought by an operating firm/other investors or an IPO). This results in a dummy variable representing an investment exit because the firm ceased operations. Such an exit event stands for a negative consequence from escalation behavior for the business invested in. Due to the dichotomous nature of the variable indicating the consequence of escalation for the firm a logistic regression analysis is executed. Hypothesis 8a and 8b are tested independently and a complete model consisting out of all variables to tell if these can be accepted or not.
Control Variables
In total 4 basic control variables are applied in all tests that involve the business angel in persona. At the individual level of the investor, age and education are controlled for due to their distinctive influence on investment behavior (Wiltbank et al. 2009). Age is treated as a continuous variable by subtracting the year of birth from the current year. Education is measured in 4 categories (no academic education, bachelor, JD and master and higher) and therefore transformed into dummy variables per category. Both of these variables are not controlled for in testing hypothesis 8 since the firm is the subject of investigation here.
spread risk and are therefore more likely to reinvest (Neher, 1999). Another control variable in this category is the total amount invested by the business angel. Accordingly this is a crucial and widely confirmed antecedent to escalation behavior (Sleesman et al. 2012; Staw, 1976). Also Wiltbank’s research (2009) already exposed that multiple types of experience (e.g. entrepreneurial) significantly influence the total amount that is invested and will be controlled for to take away the effect it has on the depending variables. The investment experience and total investment size are both deployed in all models for testing each of the hypotheses.
Conclusively it is important to control for the % of wealth the business angel is depositing in this investment to get the perceived indication of the investment size for the business angel. This is important because of the differing reference point (as % wealth invested) per business angel as specified in the prospect theory (Tversky & Kahneman, 1979). This variable is only relevant for hypotheses 1a to 6a and 7 because of its financial outcomes and not relevant for the amount of time invested and exit type for the firm.
At the firm level the control variables consist out of the industry the company is operating in and the strategies the business has implemented during the investment. The string variable accounting for the industry of the investment to account for the performance differences across industries. This variable is also transformed into dummy categories consisting out of 8 industry types (software, health and medical, retail and consumer goods, industrial and semiconductors, media and entertainment, business, ICT and hardware and other industries) and will be controlled for in all hypotheses tests. Ultimately 5 types of firm strategy are included as dummy variables to imply if such a strategy is adopted or not (attaining cash flow, acquiring necessary resources, focus on flexibility, focus on sticking to plan and a strategy around positioning the venture). These control dummies will only be relevant fir hypothesis 8 because the consequences for the firm are the point of interest here.
Results
The descriptive statistics including means, standard deviations and Pearson correlations are presented in table 2. Out of the total population 663 of the business angel investments included investment amounts (variable 7: total amount reinvested), which infers that little over half of the cases are suited to be implemented in the analyses. On average the amount of management and entrepreneurial experience is roughly the same, however experience in the industry of the investment is on average fairly lower. The typical business angel investment is done by at least five individuals and includes more than 60 hours of due diligence prior to investing. We can also see from the binary variables that the majority of the sample invests in the early stages (75%). The mean value for the total amount reinvested lies above $40.000 in combination with a total time span of little under 3.5 years. To conclude on the descriptives the average investment outcome is positive and even over $300.000. However almost 1/3 of the investment exits are accompanied with the firm ceasing its operations (32.5%).
The correlation matrix including the independent variables exhibits no alarming values (significant correlations < 70% correlating) among these before testing the hypotheses.
Antecedents
The hypotheses are tested through 4 regression models, one for each of the dependent variables. The first model tests hypotheses 1a up to 6a for the total amount reinvested as the outcome variable through linear regression. For hypotheses 1b to 6b the continuous variable indicating the length of investment
represents the outcome in a linear regression model. Each of the independent variables that embody an escalation determinant, in combination with the control variables, was introduced into the model individually. Ultimately a full model consisting out of all independent and control variables is applied. The results of the analysis for hypotheses 1a to 6a are found in table 3, the results of
1b to 6b are reported in table 4.
Even though high, significant F-‐scores and R square values are attained indicating a good fit, the model with the amount reinvested as dependent variable displays no strong significant regressions in the single effects model.
Weak evidence is found for investing in the early stages of the company with a strong coefficient (B=22.214, p<.10). The strong coefficient can be explained by the dichotomous nature of the seed/start-‐up stage investment and confirms that investing in these stages increases the amount reinvested. Additionally the results for the full model (on the a hypotheses, located in the final column of table 3) allow us to accept hypothesis 6a (B=33.659, P<.05) with a moderate regression relation. Accordingly the coefficient is even stronger than in the single effects model signifying higher reinvestment amounts when
Table&3&Regression&analysis&of&antecedents&on&the&total&amount&reinvested&(x1000)
Independent'variables H1a H2a H3a H4a H5a H6a Full,model,a
1.&Management&experience 0.193 1.278* (0.525) (0.742) 2.&Entrepreneurial&experience 0.790 1.540 (0.609) (0.855) 3.&Industry&experience 70.487 70.894 (0.553) (0.702) 4.&#&of&coJinvestors 1.930 1.540 (1.362) (1.487) 5.&Hours&of&due&diligence 70.014 70.011 (0.016) (0.017) 6.&Invested&in&seed/startJup&stage 22.214* 33.659** (11.90) (15.305) Control'variables Age 0.892 0.669 0.909* 0.889 0.682 0.969* 0.452 (0.560) (0.554) (0.550) (0.631) (0.556) (0.543) (0.793)
Education&dummies Included Included Included Included Included Included Included
Industry&dummies Included Included Included Included Included Included Included
