Overconfidence in SMEs

This chapter presents an overview of the overconfidence construct. Stemming from the behavioral finance literature, the overview discusses overconfidence as a result of several cognitive biases. In particular, there is a detailed discussion on the self-serving bias, the valence effect, the wishful thinking bias, and the anchoring effect. These biases have a detrimental effect in business and financial decisions. The chapter then presents the Big Five Model, as a model of interpretation for human personality. This model encompasses extroversion, friendliness, conscientiousness, emotional stability, and open-mindedness. All these elements are salient when determining overconfidence. After a discussion on the implications of an overconfident attitude in the stock market, there is a clear discussion on the behavior of the overconfident manager. The chapter concludes with the impact of overconfidence for small and medium enterprises. The ideas developed here are a base for the in-depth contextual analysis of the subsequent chapters.

This chapter uses budget forecasting to highlight (i) if entrepreneurs make on average inaccurate predictions, (ii) the possible drivers of inaccuracy, (iii) the managerial implication of this biased attitude. The study empirically analyzes a sample (N = 151) of a peculiar context: small and medium non-financial Italian firms. We argue that what drives inaccuracy is an overconfidence attitude. Several independent variables are collected to capture and explain the potential underlying mechanisms: individual characteristics, such as entrepreneur’s gender, age, and educational level and contextual characteristics, such as the firm’s organizational structure and the processes of administration and control. The variation between budget and final balance sheet of EBITDA, equity, and borrowing costs are used as dependent variables. We find that when entrepreneurs decide without a joint committee, biases are more pronounced. Interestingly, we show how the proper implementation of an integrated software system increases substantially forecasting accuracy. Focusing on a peculiar geographical area affected by the recent crisis, this chapter elicits for the first time overconfidence in SMEs through forecast predictions in the annual budget.

In this paper, we investigate the relation between confidence and sport performance of women in a predominantly male task. We also study the accuracy of predictions and the implications of potential biased predictions in terms of overall happiness. Our main claim is that women underestimate their result because of the uncertainty related to the performance and because of defensive pessimism, a strategy used to cope with the chance of failure. To test our hypotheses, we conducted two field experiments with players. The first experiment was a two-stage experiment. In the first stage, participants were asked to judge their individual future performance and to place themselves among others, estimating their percentile position. In the second stage, participants rated their feelings about their personal outcome in terms of happiness. The second experiment extends the study to a masculine environment and introduces an incentive to measure if there is a conscious decreasing of expectations. We show that in predominantly male task, women explicitly and consciously decrease their expectations to protect themselves. The analysis suggests that coaches should accept women’s pessimism before a performance, because it is a conscious way to handle with the anxiety of the assessment.

This chapter summarizes the main contributions on the overconfidence phenomenon discussed in this monograph. It also provides the key literature to offer the reader an in-depth analysis of the phenomenon in business and beyond. The starting point, after discussing what is overconfidence and how it can be measured, revolves around the implications of an overconfident attitude in small business management. This chapter goes further in discussing ways to reduce overconfidence when hubris and the excessive use of heuristics kick in. In this sense, it presents the advantages of using integrate software systems to reduce overconfidence. To further assess the impact of overconfidence in day-by-day decisions, the chapters present the findings on overconfidence in another different domain, sport, where women show the opposite bias, underconfidence, because of the uncertainty related to the performance and because of defensive pessimism, a strategy used to cope with the chance of failure in a male-dominated task. Across the brief chapter, there is a holistic discussion on how to improve accuracy in judgment and some key methodological routes to actually be able to measure overconfidence. Specifically, the book as a whole discusses how to conduct experiments, use large secondary datasets or psychological scales to assess the phenomenon from a different angle. The approach of this chapter and the citations used are at the interception between psychology and entrepreneurship, This chapter closes with a manifesto in 11 points.