Entrepreneurs, As Distinct From Firms: E-Space And F-Space--论文代写范文精选

两种现象也没有理由不能同时存在。但异质性无法解释为什么企业家连续性是一个有用的策略。特别是,学习效果和积极的路径依赖性是连环创业可行的来源。一个聪明的企业家,我们假定,从他们的失败和成功中学习。在下面的essay代写范文进行论述。

Abstract
We have argued that serial entrepreneurs can succeed even if some (but not all) of their firms fail. This relaxed requirement for success is based on the suspicion that the ‘probability of entrepreneurial success’ can be greater than the ‘probability of firm success.’ Of course, underlying sample spaces, measures, and criteria for what counts as success all need to be specified before such suspicions can be either confirmed, rejected or quantified. But we will not embark on a detailed operationalization of each of the above issues here; nor will we debate the merits and demerits of specific criteria and/or statistical tests; instead we will focus on clarifying the larger perspective and making it more precise for use in future empirical work. The problem of determining the rates of failure for entrepreneurs from that for firms is complicated with the usual confounding issues that plague cohort analysis over heterogeneous groups (Vaupel and Yashin 1985), (Haunsperger and Saari 1981). The focus of this section, however, is the following question: What specific aspects of seriality help reduce the failure rates for entrepreneurs as compared to that for firms?

Connections of above implications to extant evidence 
The fact that our analysis leads us to the negative binomial distribution as the connecting link between E-space and F-space is cause for comfort and confidence in the validity of our approach. The negative binomial is the classic contagion distribution, going all the way back to the origins of the subject (Greenwood and Yule 1920). It is one of the simplest possible distributions that can be associated with Gibrat’s law which forms the basis for other contagious growth distributions such as Zipf’s, Pareto’s, Geometric et cetera. The importance of Gibrat’s law in economic phenomena such as the size distribution of firms has been amply evidenced by Simon (1955), and Ijiri and Simon (1975). Needless to say, the negative binomial distribution does not rule out the possibility that the real underlying phenomenon might be heterogeneity in the entrepreneurial population. 

There is also no reason why both phenomena cannot exist concurrently. But heterogeneity cannot explain why seriality is a useful strategy for entrepreneurs. In particular, both learning effects and positive path dependencies are viable sources of contagion in serial entrepreneurship. An intelligent serial entrepreneur, we posit, can learn both from their failures and successes; in fact, in explicating the theory of effectuation based on studies of entrepreneurial expertise, Sarasvathy (2001) has argued that, …effectuation posits a plurality of “failed” firms for any one or more “successful” firms that actually get created by any given entrepreneur. The normative aspects of effectuation, if any, for the creation of successful firms would have to do with the “management” of failures, rather than with their avoidance. 

Similarly, successes too provide useful lessons for the serial entrepreneur. Furthermore, successes also enable and sustain certain positive path dependencies such as persistent social networks, increased financial and reputational resources, and access to useful corridors for future opportunities. The fact that entrepreneurs are not passive subjects of event streams, but instead impress their will on them, strongly suggests that serial entrepreneurship is best modeled as a result of contagion processes rather than say, by mixture models. These questions, the robustness of the models outlined here, the intriguing connections with Polya urns, the insights that are to be found in accident theory, reliability 22 theory and the statistical analysis of heterogeneous groups are all items that await systematic and sustained study.

Summary And Possibilities For Future Work 
In this paper we set out to investigate if we can say anything more about entrepreneurial success and failure than the oft-repeated, well-accepted, and pragmatically bankrupt bromide, “Most firms fail.” A careful exploration of the empirical work to date on this issue revealed the existence of two distinct probability spaces -- the space of firms (F-space) and the space of entrepreneurs (E-space) -- and the fact that the two were often confounded in the designs of the studies. This confounding ended up clouding the results of the studies and made interpretations of the results either irrelevant or unusable.

Delving deeper into the two spaces and the relationship between the two led us to the following three key findings: 
1. Probabilities defined over E-space may assume different values than probabilities defined over Fspace. Accordingly, decision making in E-space is not necessarily identical with decision making in F-space. 
2. Serial entrepreneurship can be modeled as a temporal portfolio with contagion effects, leading to the argument that the seriality provides a viable strategy for the entrepreneur to improve his or her own expectations of success, over any given success rate for firms. 
3. A population of serial entrepreneurs would very much look like the economy we actually observe empirically – i.e. size distributions of firms in such an economy would conform to Gibrat’s law.

In sum, our analysis leads us to challenge the received wisdom that firm successes and failures determine the successes and failures of entrepreneurs. In fact, we contend that entrepreneurs can use firms as instruments to increase the probabilities of their own success. This contention has larger implications for entrepreneurial learning that have to be investigated and developed through future work. In fact, in the interests of an uncluttered exposition of a new conceptualization of entrepreneurial success and failure, we have altogether ignored the treatment of specific learning effects and or path 23 dependencies. 

But clearly this has to form a vital area of inquiry into the phenomenon of serial entrepreneurship and in the further development of our model of it as a temporal portfolio of firms. This approach suggests a way for entrepreneurship scholars to pick up the gauntlet that Arrow threw down (quoted at the beginning of this paper). Perhaps the surest way to falsify his null hypothesis - - that there is no particular set of individual or institutional characteristics that separate the failures and successes -- is to accept it. This is not a paradox. We only need to understand that the null hypothesis does not exclude the possibility that all entrepreneurial individuals and institutions can succeed by exploiting contagion processes embedded in serial entrepreneurship, irrespective of the null hypothesis being true for firms.（essay代写)

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