Abstract
This paper provides a detailed exploration of the methodologies, findings and conclusions of five researchers in the area of entrepreneurship and the various factors that impact on it. The aim of this review is to support the research that on “Motivational Factors of students becoming Entrepreneurs using a push-pull theory of Entrepreneurship.” This review explores issues such as social capital and cultural capital and how they reinforce entrepreneurial development. Further, this review explores risk-taking and the factors surrounding it. The research concludes the risk-taking in entrepreneurship involves not only an examination of the returns, but also the duration during which the returns will be spent. This finding underlines the fact that people favor returns that can be spread out over a long period than windfall gains. Further, the paper reviews the extent to which interaction in social media sites such as Facebook contribute to peer influences with regards to entrepreneurship.
Light & Dana (2013) in their research article titled, “Boundaries of Social Capital in Entrepreneurship,” examined the role played by social capital in entrepreneurship with the objective of determining whether social capital can be effective without cultural capital. Their methodology adopts a two-pronged approach. First, they examine and critique various literature that explore the role that social capital play in entrepreneurship (Light & Dana, 2013). Secondly, after critiquing the literature, Light & Dana examine the community at Old Harbor, Alaska that comprises mainly of Alutiiq people (Light & Dana, 2013). Data was collected through various data collection methods such as audiovisual recordings and photographs. The researchers wrote the impressions derived from these recordings. Respondents discussed answers as they deemed most comfortable. The project was implemented between the years 2004 and 2010. The researchers used triangulation and combined all the material to brainstorm theory building. Although this community has abundant social capital that they used for economic purposes, Light & Dana note that they did not use it for commercial entrepreneurship (Light & Dana, 2013). The results indicated that 95% the Alutiiq people, all self-identified as entrepreneurs. Out of these, 69% were mono-racial solidarity (Light & Dana, 2013). Only 5% were multi-ethnic or Euro-Americans and not Alutiiq (Light & Dana, 2013).
Light & Dana (2013) explore the claims by some researchers that social capital can be suppressive of entrepreneurship when the dominant group keeps the subordinate group from the benefits of influence, information, and solidarity (Light & Dana, 2013). As such Light & Dana discuss the question whether social capital acts as a catalyst of an obstacle in certain settings. To summarize the claims made in different studies, Light & Dana categorize the findings into pros and cons arguments regarding social capital. On the pro side, they highlight the claim that resources derived from social capital enhance and enable group entrepreneurship where the groups are endowed with social capital (Light & Dana, 2013). However, Light & Dana indicate that one weakness of this claim is that the research literature used relies too much on the prevailing social contexts in which entrepreneurship is underpinned by social capital, thus concealing the underpinning role that cultural capital plays in entrepreneurship (Light & Dana, 2013). To test the positive side (pros) highlighted by the various studies reviewed in the paper, the researchers identified a group with high social capital, whose abundance in the social capital did not necessarily support their commercial entrepreneurship. A suitable group for this approach was the Alutiiq people (Light & Dana, 2013). The findings showed that in the absence of cultural capital, social capital did not act as a catalyst for commercial entrepreneurship for the Alutiiq people, but a barrier. In summary, the research concludes that social capital only fosters entrepreneurship when supported by cultural capital (Light & Dana, 2013).
The findings from this research apply to my research because they explore the social capital and how it can reinforce the entrepreneurial development of a given community. However, it introduces a cultural element to the discourse on social capital, indicating that for social capital to be effective, it has to be underpinned by cultural capital. This research is in keeping with the findings from other researches highlighted in this paper. For example, it mirrors the findings in Guiso et al. (2002) that areas that are rich in social capital are exposed to a wide array of financial instruments. This study shows that explorations of the effects of social capital and its support of entrepreneurial development should consider the necessary symbiosis with cultural capital that must exist. This research shows that less dominant groups in areas of high social capital can bridge the gap between them and dominant groups to access their social capital. In this regard, Light & Dana (2013) indicate that “The United States has had an unparalleled, successful history of assimilating minorities.” This statement means that even minorities can gain from the social capital of the dominant group. Similarly, young people who wish to be entrepreneurs can bridge the gap between themselves and established entrepreneurs to obtain benefits from their social capital. This social capital may include business connections and reputation. To bridge this gap, young people can prove their trustworthiness to established entrepreneurs in return for social capital in the form of referrals, advice, and loans.
Van Praag & Booij’s study titled “Risk Aversion and the Subjective Time Discount Rate: A Joint Approach (2003) seeks to find how willing people are to take risks as based on influencing factors such as age, gender, income, education, the degree of religious participation, the Quetelet index of the individual, entrepreneurship, and other variables (Van Praag & Booij, 2003). The research shows that young people are more willing to take risks than older people. These researchers sought to analyze risk aversion and time preference discount rate of every individual from a large sample of individual answers to six lottery questions (Van Praag & Booij, 2003). The objective was to discover the degree to which people are risk averse as dependent on factors such as income, gender, time preference, etc. This study employed a sample of 8,000 anonymous respondents to which they ask for a bidding price for six separate lotteries. The use of six lotteries provides the opportunity to simultaneously identify the approximate value for the relative risk aversion for a particular respondent, γ (Van Praag & Booij, 2003). Also, it is easy to identify the subjective discount rate for a respondent ρ. The researchers established that a correlation of -0.35 exists between the values γ and ρ. The variations in ρ and γ can be explained through individual characteristics such as gender, education, income, the degree of religious participation, the Quetelet index of the individual, entrepreneurship, and other variables (Van Praag & Booij, 2003). This approach has the weakness that the absence of real rewards or losses possible from this undertaking may have made the respondents answer the questions in ways that are not genuine. However, this issue was sorted by dropping the respondents who answered questions irrationally (Van Praag & Booij, 2003).
This study used questions to six lotteries (In the context of my paper, the use of lotteries is a good proxy for entrepreneurial undertaking. The questions began by informing the respondents of the prize money to be won in the fictitious lottery, the number of participants (hence the probability of winning), and the fact that the prize is an amount of money equal to the respondents monthly income. The question is then posed: How much are you willing to part with for the ticket? (In Dfl.)_____. The six lotteries are different in chances π, equivalent to 1/5, 1/10, and 1/100. They are also different regarding size.Four of the prices come in absolute amounts that range between DFl. 1000 and Dfl. 1.000.000.The highest prize is large and equivalent to about 10 to 15 years worth of income for the majority of the respondents. This study relies on a model (Van Praag & Booij, 2003). The model is based on the assumption that a typical respondent with a net monthly income of y gets an offer to take part in the lottery with a prize Z and probability π of winning. The ticket price is denoted as Ӑ, and the utility function of the respondent is U(·).The model holds that if the respondent’s individual preferences are in keeping with the Von Neumann-Morgenstern (NM) maxims or rules, the utility of accepting the offer expected will be
π) U(y – Ӑ) + π U(y – Ӑ + Z).(1).
The study results implied that in cases where people would like to invest in a particular venture (which in the case of the study was a lottery). They consider not only the risk involved but also a time dimension. This statement means that they do not only evaluate the prize money on it an absolute value, but also on the manner in which the prize may be spent gradually over time. This factor plays a more significant role for large prizes than for the smaller ones. This study is relevant because it shows that while considering investment, people consider not only the risk involved, but also the manner in which, or the possibility that the gains can be spent over time. This study also shows that young people are more likely to take risks than older people. These findings may be explained by the fact that young people are less cautious and take more risks because they have fewer commitments than older people (Van Praag & Booij, 2003).
Pempek, Yermolayeva, & Calvert (2009) conducted a study in which they sought to describe the amount of time college students use social networking sites, why they used them, and how they used them. This study is relevant because it adds to the literature on young people’s use of social media for interaction and other activities. For example, it uses a diary-like method to try and give a detailed and accurate assessment of time use. The study analyzed a rich set of answers to open-ended questions with the view of clarifying why students used Facebook. This information was enriched using survey information on the activities that students perform on social media (Pempek, Yermolayeva, & Calvert, 2009). The nature of the social interactions on Facebook is also described. The hypotheses that were formulated include the statement that young adults use Facebook mainly for social interaction. The study employed 92 undergraduate students where 60 were females, and 32 were male (Pempek, Yermolayeva, & Calvert, 2009). The mean age was 20.59 years with a standard deviation of 1.07. After completion of a consent form, applicants were issued with a diary-like measuring instrument with seven time use questions (each per day) and a checklist with 7-day activities to indicate their Facebook use. Each participant was requested to complete the checklists each evening. The amount of time spent on Facebook was assessed every day through a diary-like measure. Each respondent indicated the amount of time spent on Facebook every day for one week and the specific activities that the participant did for each day during the one-week period (Pempek, Yermolayeva, & Calvert, 2009). There were 25 main activities included in this checklist. These activities include looking at photos, posting photos, reading the posts on one’s wall, posting on walls, and reading the posts on other people’s walls. After handing in the diary measure, students were asked to complete the survey. Students answered questions regarding their Facebook activities within the “past week.” The questions employed a 4-point Likert scale with the continuum items of “ a whole lot,” “Quite a bit,” “some,” and “not much.” The questions were based on the 25 items contained in the checklist. After statistical analysis, the results indicated that participants used Facebook to establish personal identity. Also, students indulged in group membership even though they did not participate actively in these groups. A major finding from this research is that students “Lurked” or spent time looking at what other people said about certain issues and how they reacted to ideas. The significance of this finding is that shows that students who use social media may be influenced to behave in a certain manner by their peers. In this regard, social media, particularly Facebook, becomes an important environment in which young people can be influenced by business activities including the taking of risks. This study is also in keeping with the findings of Ryder (1965) that social change comes from changes in groups of young individuals that have common experiences. Also, there is an increase in the extent to which role peer effects contribute to actions in young people. The age of young people to become business entrepreneurs is considered a pull factor just as their desire to achieve their ambitions at an early age is an indirect or direct result of their age. This study is also applicable because it supports the notion that interactions through the internet can reduce the barriers to entry in business considerably. It is also in keeping with the findings that the influence of the entrepreneur’s peers is crucial to the entrepreneurial process (Birley, 2000). The interaction between peers acts as social capital because it influences their ability to obtain and apply ideas as well as funding. Social networks may also help to support the entrepreneur by keeping them appraised on the possible risks and opportunities available.
Guiso et al. (2000) sought to establish the influence of social capital on financial development. They exploited the well-known differences in trust and social capital in different regions of Italy, relying on macroeconomic data on firms and households. Guiso et al. (2000) used data from two surveys on firms and households. One of these was the Survey on Households Income and Wealth (SHIW), which contained information regarding portfolio decisions, employment of financial contracts, and detailed individual and geographical characteristics of a large sample comprising 32,700 households. The second survey used was the Survey of Manufacturing Firms (SFM), which shows information on access to credit as well as ownership structure. It also shows firms’ demographics. The researchers employed a measure of civicness, which was justified by the fact that social capital, trust, and a measure of civicness had a very close correlation. Guiso et al. (2000) relied on various specifications and samples and controlled for various geographical and individual characteristics. They studied the effect of the level of trust on the portfolio allocation and use of checks in households, availability of loans to firms and households, the ownership structure of firms and reliance on informal lending (Guiso et al., 2000).
Their findings indicated that in Italian regions that reported social trust high levels, households preferred to invest more in stock and less in cash. They also used more checks, had higher levels of access to institutional credit and made less use of informal credit. Low trust regions indicate more intense dependence on transactions within small subgroups like families and friends. The research shows that the probability of receiving a loan from a family member or friend is decreasing in the degree of trust that prevails in the area. Guiso et al (2000) also indicated that in these regions, the effect of trust was stronger in cases where law enforcement was weaker and prevalent among less-educated people. They also concluded that the behavior of movers was mainly influenced by the degree of trust in the environment where they lived. However, a significant fraction of the effect could be attributed to the level of trust that prevailed in the provinces in which they grew up (Guiso et al., 2000).
The research by Guiso et al. (2000) applies to this paper because it shows that access to funding is dependent on the level of trust between the financier and borrower. The study shows that the environment in which one is located determines their level of social capital. It may also determine their ability to get loans or funding. This observation is explained by the fact that the level of trust that the financier has on the borrower is affected by geographical factors. For example, in areas where law enforcement is weak, the level of trust is high. In the context of the paper, these factors mean that the environment in which one exists can affect their ability to receive crowd-funding for their projects or entrepreneurial activities.
Richard Florida in his report, “The Rise of the Creative Class,” indicates that the best approach to economic growth is based not only on the ability for cities to attract the creative class, but also to translate the accruing advantage into economic outcomes through new ideas, regional growth and new high-tech (Florida, 2002). Florida presents a new measure known as the Creativity Index. This index employs four equally weighted factors: workforce share of the creative class, high-tech industry, innovation (patents per capita) and diversity. Diversity is measured through the Gay Index. The researcher views the Gay Index as a suitable proxy to show a region’s openness to different ideas and people. These set of measures, according to Florida together form a barometer of any region’s long-run economic potential. In various tables, Florida presents a creativity index ranking that shows the top 10 and lowest 10 metropolitan regions. He has grouped these regions into three sizes, Large, medium, and small regions/ cities. Florida supports his creativity index approach using real-life examples of people who chose to live in certain areas as opposed to others because of the diversity that these regions offered. These people, according to Florida, felt that they would thrive socially and business-wise in areas that had high diversity indices (Florida, 2002). He refers to such areas as “plug-and-play communities” because one needs to simply move to these areas and begin their ventures. This article is crucial to my research because he shows that 30% of the American Workforce generates an average income of $48,782 per individual annually, while the blue-collar worker generates $28,000 (2002 figures). Florida also notes that young people are more prone to risk-taking than their older counterparts. The main challenge to the validity of this approach is that is largely untested over many years and relies on measures that are somewhat arbitrary.
References
Birley, S. (2000). The role of networks in the entrepreneurial process. In Small business: Critical perspectives on business and management, ed. D. J. Storey, 1495–508. London: Routledge.
Florida, R. (2002). The rise of the creative class. New York: Basic Books.
Guiso, L.; Sapienza, P.; and Zingales, L. (2004). The role of social capital in financial development. American Economic Review 94: 526–56.
Light, I. and Dana, L. (2013). Boundaries of Social Capital in Entrepreneurship. Entrepreneurship Theory and Practice, 1(2), pp.1-22.
Pempek, Tiffany A., Yevdokiya A. Yermolayeva, and Sandra L. Calvert. (2009). "College students' social networking experiences on Facebook." Journal of applied developmental psychology 30.3: 227-238.
Van Praag, B. M. S., and Booij, A. S. (2003). Risk aversion and the subjective time discount rate: A joint approach. Working Paper No. 923. Center for Economic Studies and Ifo Institute for Economic Research, Munich, Germany.
