FAILING FIRMS AND SUCCESSFUL ENTREPRENEURS: SERIAL ENTREPRENEURSHIP AS A SIMPLE MACHINE

Given what we already know about firm success and failure, namely that most firms fail, can we say anything about the possible success or failure of entrepreneurs? In this paper we argue that irrespective of what we believe the failure rate of firms to be, we can still rigorously understand entrepreneurial success/failure and derive useful prescriptions to improve success rates of entrepreneurs. Particularly, entrepreneurs can use Bayesianism as a control mechanism, instead of as an inference engine. “Most firms fail,” appears to be a consensus among entrepreneurship scholars and practitioners alike, even when they disagree on the actual proportions (Aldrich & Martinez, 2001; Fichman & Levinthal, 1991; Hannan & Freeman, 1984; Low & MacMillan, 1988; Stinchcombe, 1965). Estimates of firm success rates range from the highly disputed but optimistic 44% of Kirchhoff (1997) to the widely acknowledged one in ten of the National Venture Capitalists Association. Under these circumstances, economists such as Arrow are not easily refuted in their claims about the irrelevancy of business school programs that profess to “teach” entrepreneurship: Are we trying to isolate a claim that some particular set of individuals with certain characteristics or particular set of institutions create -distinguish the successes and the failures? And this introduces me to what I call the null hypothesis: That there is no such thing. Such a null hypothesis begs the question as to why any entrepreneur would ever start a firm, to say nothing of the serial entrepreneur who starts several, both before and after successes and failures. To that the economist normally replies either that the entrepreneur is extraordinarily risk loving, or that he or she operates under the illusion that the expected value of the payoff (estimated expected return multiplied by their subjective probability of success) is high enough to spur entry – or both. There is credible empirical evidence that the former explanation based on a supra-normal preference for risk, cannot be justified. Entrepreneurs have been shown to range all over the risk preference spectrum and the distribution may even be skewed toward risk aversion rather than otherwise (Brockhaus, 1980; Palich & Bagby, 1995; Sarasvathy, Simon & Lave, 1997). 1 JBV Transcription of Report on the seminar on research perspectives in entrepreneurship. Journal of Business Venturing, 15(1). As for the latter (that the expected payoff is high enough to spur entry), there are no studies on how the entrepreneur estimates his or her subjective probability of success or failure. Nor are there any studies that indicate how they ought to estimate such a probability. One reason for this omission could be the extraordinary difficulties in even estimating the rates of firm successes and failures. Problems range from hindrances in data collection especially about failures, to incompatibilities in the complex taxonomy of firm characteristics that make definitions of rates of success or failure meaningless. For example, how can one compare the success of a bed and breakfast in Vermont with that of a bio-tech startup in Seattle? Therefore, the overall practice of the extensive literature on estimating rates of firm success/failure is to unwittingly or explicitly equate the expected success rate of firms with the expected success rate of entrepreneurs. This leads us to the central question of this paper: Given what we already know about firm success and failure, namely that most firms fail, can we say anything about the possible success or failure of entrepreneurs? In the following pages we argue that irrespective of what we might believe the failure rate of firms to be, we can still rigorously understand important relationships between entrepreneurial success and failure and derive useful prescriptions to improve the success rates of entrepreneurs. We begin our investigation by reviewing three streams of literature to summarize what we know about entrepreneurial success. Next we examine the space of entrepreneurs as distinct from the space of firms and discuss the transformation of measures between the two, as described by Bayes’ formula. Critical to our exposition is the reinterpretation of Bayes’ formula in terms of control rather than prediction, that is, as a tool for shaping events rather than for updating beliefs. WHAT WE KNOW ABOUT ENTREPRENEURIAL SUCCESS/FAILURE Success rates of firms and entrepreneurs have been studied extensively by a variety of researchers under a number of rubrics such as: firm formation and entry (by scholars in industrial organization); organizational founding and survival (by population ecologists and organizational theorists); and, entrepreneurial success and failure (by entrepreneurship researchers). We now examine each of these areas and summarize their findings to show that all of them either confound the spaces of entrepreneurs and firms, or focus exclusively on the space of firms. From Studies of Industrial Organization Following a plea by Edwin Mansfield (1962: 1023), to encourage econometric studies of the birth, growth, and death of firms, a slew of industrial organization scholars began studying the process of entry with a view to understanding its determinants as well as its impact on market performance. In an excellent review of this stream of research, Geroski (1995) summarizes the results as a series of stylized facts that are generally agreed upon by scholars in the area. For our particular purposes in this paper, the key facts from this body of work are: (a) While entry is common, survival is not. In other words, while large numbers of firms enter most markets in most years, survival of new entrants, especially de novo entrants, is low; and, (b) Most markets are subject to enormous waves or bursts of entry in the early stages of their life cycles. From Studies of Population Ecology of Organizations The above two results culled from industrial organization are independently supported (at least partially) by organization theorists who use an evolutionary and/or population ecology perspective (Aldrich & Fiol, 1994). Population ecologists have found that success rates of organizations are age dependent. As concisely summarized by Henderson (1999), this literature does not always agree on the exact relationship between the age of a firm and its probability of success or failure. While some stress the liability of newness as a factor of firm failure (e.g. Stinchcombe, 1965; Hannan & Freeman, 1984), others argue that there is an early window of survival due to the initial stock of assets acquired at founding after which the liability of adolescence takes over and reduces the life expectancy of firms (Bruderl & Schlussler, 1990; Fichman & Levinthal, 1991). But besides the high probability of infant (or adolescent) mortality, this literature also finds a high probability of failure due to old age when firms tend to become highly inertial and misaligned with their environments (Baum, 1989; Barron, West & Hannan, 1994). Neither the industrial organization literature, nor the one based on population ecology addresses the success or failure rates of entrepreneurs. From Entrepreneurship Research Entrepreneurship scholars do worry about entrepreneurs as well as firms. All the same, it is in this literature that the greatest confounding between firms and entrepreneurs occurs. For example, there is a rather large stream of effort in this literature devoted to the traits and characteristics of entrepreneurs and how they affect firm performance. In a comprehensive review of this stream, Gartner (1988) identified a number of studies starting around the middle of the twentieth century that focused on the personality of the entrepreneur as a predictor of firm success. He argued for the futility of the traits approach since it sought to separate “the dancer from the dance” and in over three decades did not result in any clear understanding of the phenomena concerned with firm creation. Although the traits approach has since been largely abandoned, recent studies have turned to a more sophisticated understanding of the cognitive biases of entrepreneurs and their ability to garner human and social capital as predictors of firm success. Examples include Baron (2000), Bates (1990), and Busenitz & Barney (1997). Also interesting are studies such as Gimeno, et. al. (1997) that relate firm survival to factors other than objective measures of firm performance. In particular they find that subjective thresholds of performance based on human capital characteristics of entrepreneurs (such as alternative employment opportunities, psychic income from entrepreneurship, and cost of switching to other occupations) result in firm survival even in the case of so-called “underperforming” firms. All the same the focus on the personality of the entrepreneur as a predictor of firm success is not quite dead, as is evidenced by Brandstaetter (1997), and Miner (1997). The primary reason for the paucity of evidence about the success and failure of entrepreneurs as distinct from firms consists in the fact that while evidence on failed firms is hard enough to obtain (the data usually disappear along with the demise of the firm), evidence on failed entrepreneurs is well nigh impossible to come by. People just simply do not walk around with business cards that say “failed entrepreneur.” Most founders of failed firms either dust themselves off and go on to start other firms or are serial entrepreneurs who have previously been successful. Both these groups tend not to mention their failed firms except as part of uplifting anecdotes in public speeches, after the fact. The few truly “failed entrepreneurs” seemingly disappear off the face of the economy forever leaving us, entrepreneurship scholars, without any traces to follow in our pursuit of understanding them. To Sum Up, What Do We Know About Serial Entrepreneurship? The key, therefor