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Scientific and Effectuative Approaches POLITECNICO DI TORINO Master of Science in Management Engineering M.Sc. thesis work Team composition influence on decision- making process: scientific and effectuative approaches Supervisor: Prof. Emilio Paolucci Co-superv. Daniele Battaglia Co-superv. Andrea Panelli Candidate: Davide Campo March - April 2021 session “Fortuna audaces iuvat” 1 Content 1. The Decision-Making process ............................................................................................................... 8 1.1 Innovation and entrepreneurship overview ..................................................................................... 9 1.2 Scientific Method ................................................................................................................................ 11 1.3 Heuristic Search & Effectuation ........................................................................................................ 17 1.4 Team heterogeneity and other effects .............................................................................................. 19 1.4.1 The role of network ..................................................................................................................... 21 1.4.2 Psychological dimensions .......................................................................................................... 22 1.4.3 Industry effect .............................................................................................................................. 24 1.4.4 Gender effect ................................................................................................................................ 25 1.4.5 Academic level and background effect .................................................................................... 27 1.4.6 Prior experiences weight ............................................................................................................ 28 1.4.7 Stevens’ scales Theory ................................................................................................................. 29 1.4.8 Blau’s index .................................................................................................................................. 30 1.4.9 Research questions ...................................................................................................................... 31 2. The research program and its scope .................................................................................................. 38 2.1 Sampling and design experiment ..................................................................................................... 40 2.2 Why RCT design ................................................................................................................................. 41 2.3 Gauss-Markov Theorem: the OLS efficiency .................................................................................. 43 2.4 Marketing and sponsorship .............................................................................................................. 44 2.5 The data collection .............................................................................................................................. 46 3. Sample analysis and preliminary observations ................................................................................ 52 3.1 Team level aggregation and database creation .............................................................................. 60 4. Results analysis ..................................................................................................................................... 67 4.1 Preliminary evaluations ..................................................................................................................... 69 4.2 Regression presentation ..................................................................................................................... 71 4.3 Robustness check ................................................................................................................................ 82 4.4 Final conclusions ................................................................................................................................. 85 APPENDIX .................................................................................................................................................... 93 References .................................................................................................................................................... 103 2 3 Abstract A number of scholars agree that process fostered by a good task conflict entrepreneurial activities lead implicit management, meant as the concept high risks and therefore would deserve a introduced by Jehn et al. (1997, 1999) in deep study (Forlani & Mullins, 2000; Ping, opposition to the relationship conflict 2004; Eisenmann et al., 2013). A crucial management. Right such last point arises issue which must be faced nowadays is the from the evidence about control variable high failure rate and strong difficulty in called as Internal Network, which has expansion by scaling the business. given evidence that preexisting ties among According to US Census Bureau, team members can positively affect the Kauffman Foundation and US Labor decision-making process through a better Department is reported that 87% of the relationship conflict management, thus startups abandon the entrepreneurial idea mitigating divergences deriving from within seven years by the born (Fairlie and heterogeneity. Instead, the Miranda, 2017). Yet, the Thompson ambiguousness of the findings regarding Venture Economics showed that the 55% gender differences underlined the of startups receiving first financing round primary doubts claimed in the wide gets failure with economic loss, whereas literature (Phillips & O’Reilly, 1998) only the 6% is able to achieve financial produced on the argument, anyway the return five times bigger the initial prominent relationship conflict investment (Kerr et al., 2014). In order to management weight suggested by a put boundaries around the elevated number of different authors (Jehn et al. uncertainty, the researchers advise the 1997; Klotz et al., 2014; Fitzgerald et al., strategic agility utility which can derive 2017; Zhang, 2019) is here confirmed, both from structured (Ries, 2011; Camuffo thanks to what found on the internal et al., 2017) and more flexible approaches network variable and its mitigating (Sarasvathy, 2001), so that in this thesis effects. Yet, the startup team numerosity is project the decisional-making methods instead an evident proxy of how many named Scientific approach and external ties the team is potentially able to Effectuation will be explored. achieve: the more the team members are, the more they could merge their different Into the experiment of interest analyzed in contacts with the aim of creating a stable the following work, age heterogeneity and loyal business network. Referring to resulted to be positively and highly linked what written in the recent study of to the variables of interest, which are both Alessandri et al. (2018), the work linked to the decisional process. It showed engagement has been tracked and resulted to be more influencing on scientific as statistically significant throughout all approach rather than effectuative the regression models, with positive behavior: this is to confirm that the influence on both natural levels of experience diversity factor is deeply scientific and effectuative approach. crucial for the scientific paradigm, since it Additionally, as discussed by Amit (2001), puts roots on the continuous feedback also the prior experience in business plan exchange and test comparison, that is a 4 writing demonstrated to be influencing, (2019), too high academic achievements thus proving a real tie between the make become resistant to the capabilities practical business plan experience and the needed in the effectuation framework: this capabilities needed in the effectuative is what arised from who already obtained framework. Also differences in decisional a Master post-lauream or PhD, since these processes were expected when keeping two dimensions negatively related with the offering kind and industry type as effectuation. The top university levels reference (Schleimer & Shulman, 2011), seem to negatively influence the natural maybe due to the physical nature of effectuative approach maybe because the product vis-à-vis the more abstract service latter puts roots on flexibility, execution, concept. Here the offerings appear being and practical experience, namely features positively correlated with the sole being often stiffened and obstructed by scientific approach when they are services. extremely high levels of standard It can be due to the fact that the flexible academic education. In the end, the nature of the services makes easier to accumulated experience is difficult to create continuous feedback exchange with replicate and allows entrepreneurs to market and customers, so that phases of understand competitive structure and test and validation come to be facilitated market strengths, quality standards and thanks to the possibility of completing the most profitable trends. It improves entire process by only using online means, capability of performing more precise with consequent less time wasting and predictions, along with diminishing the more efficient learning. Yet, Mitchell and usually observed effects of Shepherd (2010) proved that
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