This book unifies and draws a connection to different concepts of organizational behavior, decision-making theories, psychology and strategy research. Furthermore, it focuses on the theoretical backgrounds of managerial decision-making, different personality concepts and their impact on strategic decisions. Since strategic decisions are made by individuals, it is worth analyzing to what extent personality phenomena such as hubris influence the choice between acquisitions and alliances. In fact, both governance modes are a necessary prerequisite for companies to remain healthy, gain competitive advantages and hence, become world leaders. First, this book provides a literature review of the current research status on governance modes, particularly laying an emphasis on acquisitions and alliances. Moreover, it is explored what hubris actually means, which different facets are underlying and how it is different from other related concepts, such as narcissism, overconfidence, and core self-evaluations. Subsequently, studies having dealt with the concept of hubris in general, hubris in investment decisions and hubris in governance mode decisions in particular are analyzed. Numerous of these studies on strategic and investment decision making have found managers infected with hubris to regularly overpay for acquisitions but none has yet analyzed whether hubristic decision-makers also prefer acquisitions over alliances and which decision making criteria they consider when making such governance choices. Therefore, data from students and executives are collected with the help of a policy-capturing approach - a method used to find out more about individuals’ underlying judgment and information-processing strategies. Moreover, measures to assess personality phenomena are adapted and developed. Thus, this study adds to the growing body of literature on acquisitions vs. alliances by including hitherto neglected personality variables and hence providing a richer explanation for governance decisions. Analyses are conducted with hierarchical linear modeling and logistic regression. This book closes by discussing important results, limitations and implications for both research and management.

Text Sample: Chapter 2.4.3, Theoretical Background of Overconfidence: In the psychological literature there is no overarching definition of overconfidence. Moreover, overconfidence has been defined differently in a variety of disciplines. According to Li/Tang overconfidence exists when an individual’s ex ante expected accuracy of his or her own judgments exceeds the ex post accuracy of those judgments. Campbell et al. define overconfidence as an inflated subjective probability of a particular outcome occurring which is observed as a positive difference between assessed confidence and observed achievement. Conversely, underconfidence is a condition when individuals are more accurate than they think they will be. Other scholars refer to the ‘better-than-average’ effect and explain overconfidence as an overestimation of a person’s own abilities relative to the average when assessing their own relative skill relating to one’s own personal situation. This is especially true for individuals in positions of power who are overconfident about outcomes they believe are under their control and thus overestimate their ability to create value. Because individuals expect their behavior to produce success, they are more likely to attribute good outcomes to their actions, but bad outcomes to (bad) luck. This phenomenon emphasizes the importance to distinguish between overconfidence as the overestimation of outcomes attributed to own abilities and optimism as the overestimation of external outcomes. In describing overconfidence, none of the cited studies goes beyond the most general aspects of the concept. There are several findings that are often summarized as overconfidence. However, as Moore/Healy reveal, overconfidence can be understood and measured in three different ways. In overestimation, people overestimate their actual ability, performance, level of control and chance of success. Overprecision causes people to demonstrate excessive certainty regarding the accuracy of their beliefs. Finally, overplacement means that people consider themselves to be better than others. A failure to take these non-identical concepts into account can lead to inconsistencies in findings and thus to an incomparability between different studies. Glaser/Weber identify miscalibration, the better-than-average effect, illusion of control, and unrealistic optimism as the underlying dimensions of overconfidence. Miscalibration refers to the tendency to overestimate the precision of one's information. Miscalibration is a standard measure of overconfidence in both psychology and economics. An individual is by definition calibrated if, over the long run, for all prepositions assigned a given probability, the proportion that is true is equal to the probability assigned. The better-than-average effect is similar to Moore and Healy’s overplacement concept. People, on average, tend to believe that they are better and do better than the average person without elaborately surveying their own and others’ actual dispositional qualities and abilities. Furthermore, this phenomenon reflects irrational thinking because ‘it is logically impossible for most people to be better than the average person’. Moreover, evidence suggests that these individuals also believe their risk likelihood is less than that of other people. Finally, research has shown that BTA and WTA effects are stronger when the referent is a group rather than an individual. Langer defines illusion of control as an ‘expectancy of a personal success probability inappropriately higher than the objective probability would warrant’. Consequently, it is closely connected is the concept of unrealistic optimism about future life events. The dimensions miscalibration and BTA suggested by Glaser/Weber seem to be most appropriate for the purpose of this study. As people lack self-awareness of their own knowledge, overconfidence will increase as individuals become surer of themselves. Moreover, people usually fail estimating their own level of accuracy. At the same time, the extent to which overconfidence occurs seems to depend very much on the difficulty of the judgment task which is termed the hard–easy effect. Individuals tend to be more overconfident when asked to reply to questions of moderate to extreme difficulty than to easy questions for which overconfidence seems to disappear, or underconfidence is observed. These conclusions have been heavily criticized. Also, research has proven that people do not adjust their level of confidence when participants’ knowledge of a question decreases accordingly. Especially, individuals are most prone to overestimate their performance when it is at its lowest. Thus, when questions touch knowledge areas beyond an individual’s expertise, this will usually generate the strongest potential for overconfidence. Overconfidence can lead to downplaying outcome risk or the belief to overcome it, and to engage in relatively fast decision-making. To briefly sum up, this paragraph shows that serious problems can result from the tendency to be overconfident since it can become an obstacle to effective professional decision-making. Nevertheless, a certain degree of overconfidence is necessary for achievement in life. Measuring Overconfidence: There is no overarching measurement technique to directly measure the personality trait overconfidence yet. In order to make research results comparable a widely accepted scale would be useful and is recommendable. For the purpose of this study, a scale to measure overconfidence which manifests itself miscalibration and the better-than-average effect is developed. To assess miscalibration or calibration-based overconfidence, in a typical paradigm, many factual questions are asked, and confidence in each answer is assessed. Mostly, researchers used general knowledge or domain-specific questions. Lichtenstein et al. note that the number of alternatives given can change perception of knowledge and thus, the confidence scores indicated. Nonetheless, propositions can be stated with any number of alternatives, but the confidence estimation task must be adapted accordingly by the researcher. Overconfidence is then classified as a positive difference between average confidence and average accuracy. A negative difference is called underconfidence, whereas zero difference is idealized calibration. This method is also employed by Campbell et al. who assess confidence with general knowledge questions and the participants’ confidence in their answers. According to the more specified definitions by Glaser/Weber and Moore/Healy more sophisticated measurement techniques have been developed. Miscalibration is measured with general knowledge questions whereas the investors were asked to state upper and lower bounds of 90 % confidence intervals for each question. The better-than-average effect was assessed with questions concerning skills and performance relative to others. The illusion of control score is based on the level of agreement with given statements on which the investors were asked to state scores from 1 (I totally agree) to 5 (I completely disagree), e.g. ’I never buy stocks that will underperform in the future’. A participant’s actual score was subtracted from his or her reported estimated score to measure overestimation. Furthermore, Li/Tang developed a method which is especially useful to measure a CEO’s overconfidence. Accordingly, a CEO is overconfident, the greater the difference between a CEO's subjective evaluation of his or her firm's performance and the objective performance measured as return on sales (ROS). Malmendier/Tate also introduce two measures of CEO overconfidence the first is based on a CEO's personal over-investment in their company, thus how long a CEO holds company stock options and the second is a press portrayal proxy. If a CEO persistently exercises options later than suggested by the benchmark, the authors infer that he is overconfident in his ability to keep the company's stock price rising and that he wants to profit from expected price increases by holding the options. Second, a CEO is classified as overconfident if he is optimistic enough about his firm's future performance and therefore holds options all the way to expiration (typically 10 years). Finally, since underdiversified CEOs should also avoid acquiring additional equity, Malmendier and Tate classify CEOs who habitually increase their holdings of company stock as overconfident. To further test the overconfidence analysis, the scholars collect data on CEO portrayal in the business press and identify CEOs characterized as ‘confident’ (confident, confidence, optimistic, optimism) versus ‘cautious’ (cautious, reliable, practical, conservative, frugal, steady, or negating one of the ‘confident’ terms). Brown/Sarma use a similar proxy for CEO overconfidence as Malmendier and Tate and propose that greater media coverage is associated with higher levels of overconfidence. Their measure relies on trait theory, more precisely, the Five Factor Model of Personality, in order to classify CEOs as overconfident or rational. Therefore data was collected for the same specific personality traits used by Malmendier and Tate based on the leading business press in Australia portrayed for each individual CEO. The searches also recorded the total number of articles which mention the CEO during the sample period. A measure concerning better-than-average or overplacement biases takes into account whether a participant really is better than others. There are two primary methods of assessing people’s judgments about their comparative status on a given ability, trait, or likelihood dimension. In the direct method, participants from a sample are asked to explicitly compare two things, e.g. how their standing on the dimension compares with that of others in the sample responding on a scale ranging from 1 (well below average) to 7 (well above average). Indirect measures ask participants to separately make a judgment about themselves, and an absolute judgment about others in the sample using the same absolute standard. Findings show that both better-than-average and worse-than-average effects tend to be stronger in direct measures than in indirect measures of comparative judgment.

• Managerial Decision Making

• Narcissism

• Policy-Capturing

• Overconfidence

• decision-making theories

• strategy research

Annika Lorenz, M.Sc., Jahrgang 1985, hat das Bachelorstudium der Betriebswirtschaft mit den Schwerpunkten Innovationsmanagement/Entrepreneurship, International Management und Marketing an der Humboldt-Universität zu Berlin im Jahre 2008 abgeschlossen. Im Jahr 2010 absolvierte die Autorin ihr Masterstudium in Management und Marketing erfolgreich an der Freien Universität Berlin. Bereits während des Studiums sammelte die Autorin umfassende praktische Erfahrungen in der Luftfahrt-Branche und entwickelte ein besonderes Interesse an strategischen Unternehmensentscheidungen und Persönlichkeitseigenschaften von Managern.