The Passionate Combining Entrepreneurs

Entrepreneurs are portrayed as salient drivers of regional development and for a number of years nascent entrepreneurs have been studied in a large number of countries as part of the Global Entrepreneurship Monitor project and the Panel Study of Entrepreneurial Dynamics. Scholars have devoted much effort to investigating factors that determine how individuals engage in entrepreneurial activities, with most of the discussion limited to business start-ups. However, since this type of project does not follow identical nascent entrepreneurs over time, limited knowledge exists about their development and whether they stay in this nascent phase for a long time. In practice, it is common for entrepreneurs to run a business and at the same time work in wage work, so-called combining entrepreneurs. In Sweden, almost half of all business owners combine wage work with a business. However, not all combining entrepreneurs will eventually decide to leave the wage work and invest fully in the business. Consequently, much research has focused on the first step of entering entrepreneurship full time, but less has focused on the second step, the transition from the combining phase to full-time self-employment. The aim of this thesis is therefore to contribute to the theory of entrepreneurship by gaining a deeper understanding of combining entrepreneurs and their motives and intentions.   In the context of combining entrepreneurs, the theory of identity, resources and choice overload has been used to examine how entrepreneurs’ age (when starting the business), entrepreneurial tenure (the length of engagement in the side-business), hours spent (weekly involvement in the side-business), involvement in entrepreneurial teams (leading the business with one or more partners) and involvement in networks (business networks) influence their passion for engaging in entrepreneurship while sustaining wage work. Different categories of combining entrepreneurs and their intentions have also been examined.   A survey was administered to 1457 entrepreneurs within the creative sector in two counties in Sweden (Gävleborgs County and Jämtlands County). Since there were no separate mailing lists to only combining entrepreneurs, the survey was sent to all entrepreneurs within the chosen industry and counties. The total response rate was 33.5 percent and of them 57.6 percent combined, yielding 262 combining entrepreneurs who answered the questionnaire. The survey was then followed up with eight focus group interviews and two single interviews to validate the answers from the questionnaire.   The results indicate three types of combining entrepreneurs: nascent – with the intention to leave the combining phase for a transition into full-time self-employment, lifestyle – with the intention to stay in the combining phase, and occasional – with the intention to leave the combining phase for full-time wage work and close down the business. Transitioning fully to self-employment increases with the individual’s age. Also, a positive interactive effect exists with involvement in entrepreneurial networks. The results also indicate that the ability to work with something one is passionate about is the top motive for combining wage work with a side-business. Passion is also more likely to be the main motive behind the combining form among individuals who are older at business start-up, but passion is less likely to be the main motive behind the combining form among individuals who spend more time on the business. The longer the individual has had the side-business, the less likely passion is the main motive behind the combining form, and passion is less likely to be the main motive among those who are part of an entrepreneurial team.

qtl.outbred: Interfacing outbred line cross data with the R/qtl mapping software

Background qtl.outbred is an extendible interface in the statistical environment, R, for combining quantitative trait loci (QTL) mapping tools. It is built as an umbrella package that enables outbred genotype probabilities to be calculated and/or imported into the software package R/qtl. Findings Using qtl.outbred, the genotype probabilities from outbred line cross data can be calculated by interfacing with a new and efficient algorithm developed for analyzing arbitrarily large datasets (included in the package) or imported from other sources such as the web-based tool, GridQTL. Conclusion qtl.outbred will improve the speed for calculating probabilities and the ability to analyse large future datasets. This package enables the user to analyse outbred line cross data accurately, but with similar effort than inbred line cross data.

PokerMapper: : mapping executive functions, poker playing ability and responsible gambling in online environments

Research objectives Poker and responsible gambling both entail the use of the executive functions (EF), which are higher-level cognitive abilities. The main objective of this work was to assess if online poker players of different ability show different performances in their EF and if so, which functions are the most discriminating ones. The secondary objective was to assess if the EF performance can predict the quality of gambling, according to the Gambling Related Cognition Scale (GRCS), the South Oaks Gambling Screen (SOGS) and the Problem Gambling Severity Index (PGSI). Sample and methods The study design consisted of two stages: 46 Italian active players (41m, 5f; age 32±7,1ys; education 14,8±3ys) fulfilled the PGSI in a secure IT web system and uploaded their own hand history files, which were anonymized and then evaluated by two poker experts. 36 of these players (31m, 5f; age 33±7,3ys; education 15±3ys) accepted to take part in the second stage: the administration of an extensive neuropsychological test battery by a blinded trained professional. To answer the main research question we collected all final and intermediate scores of the EF tests on each player together with the scoring on the playing ability. To answer the secondary research question, we referred to GRCS, PGSI and SOGS scores.  We determined which variables that are good predictors of the playing ability score using statistical techniques able to deal with many regressors and few observations (LASSO, best subset algorithms and CART). In this context information criteria and cross-validation errors play a key role for the selection of the relevant regressors, while significance testing and goodness-of-fit measures can lead to wrong conclusions.   Preliminary findings We found significant predictors of the poker ability score in various tests. In particular, there are good predictors 1) in some Wisconsin Card Sorting Test items that measure flexibility in choosing strategy of problem-solving, strategic planning, modulating impulsive responding, goal setting and self-monitoring, 2) in those Cognitive Estimates Test variables related to deductive reasoning, problem solving, development of an appropriate strategy and self-monitoring, 3) in the Emotional Quotient Inventory Short (EQ-i:S) Stress Management score, composed by the Stress Tolerance and Impulse Control scores, and in the Interpersonal score (Empathy, Social Responsibility, Interpersonal Relationship). As for the quality of gambling, some EQ-i:S scales scores provide the best predictors: General Mood for the PGSI; Intrapersonal (Self-Regard; Emotional Self-Awareness, Assertiveness, Independence, Self-Actualization) and Adaptability  (Reality Testing, Flexibility, Problem Solving) for the SOGS, Adaptability for the GRCS. Implications for the field Through PokerMapper we gathered knowledge and evaluated the feasibility of the construction of short tasks/card games in online poker environments for profiling users’ executive functions. These card games will be part of an IT system able to dynamically profile EF and provide players with a feedback on their expected performance and ability to gamble responsibly in that particular moment. The implementation of such system in existing gambling platforms could lead to an effective proactive tool for supporting responsible gambling.