Heurists and Biases with Habitual Entrepreneurs

Diplomarbeit von Philipp Kirchner

Introduction:

‘When making a decision of minor importance, I have always found it advantageous to consider all the pros and cons. In vital matters, however, such as the choice of a mate or a profession, the decision should come from the unconscious, from somewhere within ourselves. In the important decisions of personal life, we should be governed, I think, by the deep inner needs of our nature.’ Sigmund Freud (1856 – 1939).

Problem Statement, Research Objective and Motivation:

For almost a century the dominant idea of man in economics has been the perfectly rational utility maximizer, subsumed Homo oeconomicus. In the late 1960s and 70s Amos Tversky and Daniel Kahneman conducted a serial of experiments whose results showed that individuals make judgements that systematically violate objective norms of rationality. The findings by Tversky and Kahneman confirmed, what has been theorised before by Herbert Simon (1955), that humans are boundedly or rather approximately rational. The work of these scholars has been a major impetus for the subsequent change in idea of man across various disciplines, including economics. Kahneman and Tversky (1974) identified several broad simplifying strategies, termed heuristics that have the great advantage of speed and adaptivity in decision making, though being less accurate than objective norms of rationality. Moreover, their use often results in cognitive biases, that may lead to systematic errors in judgement. Such an entry of non-rationality into human decision behavior has lead to a more realistic assessment of how decisions are actually made by individuals taking bounded rationality and uncertainty of the environment into account.

The entrepreneurial field is an environment in which these factors are particularly prevalent, and individuals especially unprotected against. This may manifest in a higher susceptibility to heuristics and biases than by other subpopulations. Studies on decision making have shown that entrepreneurs often do use approximate strategies. Experimental results show both a higher susceptibility to some biases than other individuals and a lower susceptibility to other biases. These findings allow for the assumption of a situation or domain-specific susceptibility to certain biases. However, entrepreneurs are known to be a quite heterogeneous group, raising the question whether a type-specific proneness to certain heuristics and biases exists. To find out if this is the case it needs to be examined to what extent and why susceptibilities to certain heuristics and biases may differ between entrepreneurial types. Behavioral decision theory includes non-rational factors like experience in the set of factors that shape actual decision making behavior. Therefore it is likely that experience affects the subsequent use of heuristics and biases, which are used for entrepreneurial decision making. MacMillan (1986) introduced a typology that distinguishes between entrepreneurs, depending on their prior venture ownership experience. Founders without any previous start-up experience are termed first-time and founders who dispose of such are called habitual entrepreneurs. I am interested in if and if yes, to what extent prior start-up experience influences the use of heuristics and biases by entrepreneurs. Therefore the specific purpose of this study is to investigate differences in the use of heuristics and biases by habitual compared to first-time entrepreneurs. To my knowledge there is not any study existing, that deals specifically with this research question.

Structure of the thesis:

My contribution can be summarized as follows: Building on a critical discussion of the definitions and classifications of habitual entrepreneurship, factors will be identified that may explain differences between habitual and first-time entre-preneurs (ch. 2). These are experience, network, motivation and traits, affect and performance. After a comprehensive literature overview of heuristics and biases, their relevance for entrepreneurs shall be examined and emphasized. Of particular relevance to repeat decision making, constitutive for habitual entrepreneurs, are found the status-quo bias, the representativeness heuristic and overconfidence (ch.3). Further, the findings from chapter 2 and 3 are merged in chapter 4. Hypotheses are derived for the susceptibility of habitual entrepreneurs to the heuristics and biases mentioned before. Results indicate that habitual entre-preneurs are more susceptible to the status-quo bias and representativeness heuristic, and less prone to overconfidence than first-time entrepreneurs. Chapter 5 gives a summary and general discussion of the major findings of this work.

Table of Contents:

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Chapter 3.2, Positions in Heuristics and Biases Research:

3.2.1, The Heuristics and Biases Program:

Tversky and Kahneman initiated the heuristics and biases program in their widely cited article from 1974. They proposed, that ‘people rely on a limited number of heuristic principles that reduce the complex tasks of assessing probabilities and predicting values to simpler judgmental operations…these heuristics are quite useful, but sometimes they lead to severe and systematic errors’.

Thereby the beauty of their approach lies above all in offering ‘a cognitive alternative [to the rational choice model] that explained human error without invoking motivated irrationality’. Initial impetus for such research has been ascribed to the fact that Tversky and Kahneman observed in a series of experiments in the late 1960s and early 1970s, that even very experienced professionals, in various domains, were susceptible to certain heuristics and biases, when judging intuitively. They moreover found subjects in general to be apparently unable ‘to infer from lifelong experience fundamental statistical rules, as regression towards the mean or the effect of sample size on sampling variability’. Such observations have most likely induced the authors not to view the individual as a rational actor (any longer), but rather as a subject that makes judgments and decisions deliberately rational, while being restricted by its cognitive limitations. This concept has been named Bounded Rationality by Herbert Simon (1955). Bounded rationality is assumed by Tversky and Kahneman to evoke a reliance on intuitive, heuristic judgment where normative theory should be employed instead.

It shall be emphasized, however, that intuitive, heuristic judgment according to the authors is not just ‘merely simpler than rational models demanded [but] categorically different in kind…[thus, Kahneman and Tversky] developed their own perspective on bounded rationality’. As a reaction on expected utility theory, the methodological focus of the heuristics and biases program has been placed on when and why humans systematically err, whereas normative theory predicts decision makers to err only sometimes and non-systematically. Due to such methodological focus experiments conducted by Kahneman and Tversky often resulted in mediocre outcomes of human decision making behavior, potentially imposing the wide-spread negative connotation on heuristics. Inspite of heuristic processing leading sometimes to biased outcomes, being irrational in such cases, the heuristics themselves are according to Gilovich and Griffin (2002) not irrational, because ‘they draw on underlying processes, that are highly sophisticated’. Complementing this view the authors emphasize that heuristics in the sense of Kahneman and Tversky are ‘normal intuitive responses to even the simplest questions about likelihood, frequency, and prediction’ instead of being solely evoked by task-complexity or information overload.

Tversky and Kahneman (1974) recognize three basic, general purpose heuristics, namely adjustment and anchoring, representativeness, and availability, that are associated with specific biases. These biases are suggested to explain deviations from normative theory. In 2002, Kahneman and Frederick replaced anchoring and adjustment by the affect heuristic. They argued that the former would not be in accordance with their definition of a judgmental heuristic (anymore), since it does not work through attribute substitution (‘intuitive substitution of a complex attribute with a simpler heuristic attribute for judgment’). However, Gilbert (2002) notes that ‘anchoring and adjustment describes the process by which the human mind does virtually all of its inferential work’. Therefore all four heuristics mentioned are included in the brief overview following. All of them are broadly applicable, simplifying procedures and normally do reduce mental effort and time needed for judgment, yielding ‘quick and dirty’, though sometimes erroneous, results.

Adjustment and Anchoring:

This often applied estimation procedure involves using relevant or sometimes random information, received externally or by own partial computation, as an initial value (‘anchor’) and starting point from which on estimates are adapted successively. Thereby, final judgments of the same estimation problem will vary with different anchor values. Additionally, when using this heuristic, adjustments from the anchor are typically insufficient, yielding a bias towards the anchor.

Representativeness:

The representativeness heuristic, also called law of small numbers, describes the process of intuitive, categorical judgment by individuals based essentially on similarity. This heuristic examines to what extent a subject, object or situation is representative of a specific stereotype or comparable focal point that can be retrieved from memory. Due to such (over-)reliance on similarity, biases in judgments may occur that are based on the ignorance of relevant information like base-rates or the tendency to generalize from non-random samples like personal experience. Additionally, the use of the representativeness heuristic may entail a misconception of chance and regression, the illusion of validity and insensitivity to predictability.

Availability:

This major judgmental strategy, particularly useful in the assessment of class frequency or event probability, is used to derive the likelihood of an event by the ease or effort involved, with which it can be retrieved from memory. Since events of high probability are often more accessible, this heuristic is practical in extracting subjective probabilities of some occurrence. However, its use can lead also to some biases, due to the varying retrievability of instances and effectiveness of a search set. Additionally, the biases of imaginability and illusory correlation may occur.