Table of Contents
Introduction and Justification for the Research
Developed countries such as the UK and the US are constantly helping new entrepreneurs grow and develop their business ventures by offering support in the form of easier access to finance and business advice as well as conducting events such as the ‘Enterprising Britain Awards’ that rewards young entrepreneurs and their firms. Despite this, entrepreneurship rates in countries such as the US and the UK have been decreasing. Institutions such as the Brooking’s Institute and the Kaufmann foundation have recorded a decrease in start-up companies by 45% between the years 1978 and 2017 (based on U.S. Census data).
The definition of entrepreneurship is that “entrepreneurship is the process by which individuals pursue opportunities without regard to the resources they control” (H. Stevenson, 1983). The reason for this research proposal is to not only find out why entrepreneurship has decreased over recent years but how can we reduce it. Research into the decline of entrepreneurship will likely help in creating and implementing new policies and regulations that help guide dynamic young firms as well as reduce barriers to entry for new entrepreneurs. Research into why entrepreneurship is on the decline over recent years is crucial as entrepreneurship provides many monetary and non-monetary benefits. Job opportunities (J. Haltiwanger, 2013), stimulation of economic activity (Luttmer, 2011) and increasing economic mobility (Quadrini, 2000 and De Nardi, 2006) are just a few of the many benefits entrepreneurship provides.
Literature Review
Decker et al, (2014), Pugsley and Sahin, (2014) and Davis et al, (2007) have all documented the decrease in entrepreneurship over recent years. Despite this, research carried out has mainly defined the measure of entrepreneurship as the number of firms that enter the economy in a given year. Most research done measuring the number of entrepreneurs in an economy have included all businesses entering the economy within a year without taking into account other factors that drive successful firms such as number of employees, annual revenue and cash flow.
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Focusing on businesses with a certain annual revenue and number of employees is crucial (Stice, 2017) to ensure that results are not driven or affected by small businesses who have little to no impact on economic activity. In addition to that, Henrekson (2007) defines entrepreneurship as a synonym of being self-employed. However, measuring the number of self-employed workers is extremely hard and using this as a measure of entrepreneurship for research is likely to be inaccurate and inefficient. In 2003/2004 for example, UK tax records showed 4.5 million individuals gaining income from self-employed means whereas the Labour Force Survey (LFS) only recorded 3 million self-employed workers. This is likely because the definition of self-employed is extremely vague and people who work multiple jobs (self-employed as well as being an employee) will likely struggle to define themselves as either an employee or a self-employed worker/entrepreneur (Blanchflower and Shadforth, 2007).
Moreover, another argument for the decrease in entrepreneurship is the increase in average life expectancy. The link between an increase in average life expectancy and the decrease in entrepreneurship rates is argued by Kopecky (2017). He mentioned how as life expectancy increases and the average age of the population rises, people are less likely to risk their pensions by creating a new business or enterprise. However, it is unlikely that the decrease in entrepreneurship is directly linked to the overall increase in life expectancy. Kozeniauskas (2017) monitored the change in entrepreneurship rates between age groups (people aged between 25-35, 36-45, 46-55 and 56-65) and his research proved that instead of larger age groups having a lower decrease in entrepreneurship rates, it showed that all age groups had a relatively similar decline of about 20-25%.
In addition to that, the Global Entrepreneurship Monitor (the world’s foremost study of entrepreneurship) has argued that the difference in the personalities of age groups help dismiss this theory. Research done by the Global Entrepreneurship Monitor has showed that younger people aged between 25-34 are much more concerned with failure and risks compared to older people aged between 35-64. “The fear of failure among 25 to 34 year olds reflect a greater level of caution, and a preference for more stable employment when there is high uncertainty and a less favourable environment for entrepreneurship” (Donna Kelley, 2015). The idea that people are not starting new businesses due to the increase in life expectancy is highly unlikely. However, we must take into account that the definition of failure and risk is subjective. Different people are likely to have different perceptions of risk and failure and thus questioning a group of people on a subjective matter that is not properly defined could show incorrect and unreliable information.
In addition to that, one of the main arguments for the decrease in entrepreneurship would be the changes in trends and regulations over time. Davis and Haltwinger (2014) proposed that the main reason for the decrease in entrepreneurship in recent years would be due to the increase in federal regulations on businesses. The rise in the number of federal regulations increases the complexity and intricacy of starting as well as running a new organisation and this acts as a deterrent for people wanting to create a business (Ortmans, Kauffman Foundation, 2011). Occupational licensing for example, is a form of government regulation that requires a business/individual to carry a license in order to provide a certain product or service.
Kleiner (2015) showed the increase in occupational licensing over recent years. In 2015, 29% of all jobs in America required a license provided by the government compared to only 10% in 1975. Occupational licensing, environmental regulations and other forms of government regulations acts as a barrier to entry for entrepreneurs. Research provided by the National Federation of Independent Businesses showed that the increase in government regulation in America for businesses (from 1977-2012) increased from about 15000 to 27000 whilst the number of new employer firms per thousands of people (from 1977-2012) decreased from 2.5 to 1.3. However, we must also consider that correlation does not imply causation and that there are likely to be a number of other hidden factors driving the decrease in entrepreneurship.
Finally, Kopecky (2017) has also argued that the increase in student debt over recent years have restricted the number of students who are able to become entrepreneurs. As costs of education in countries such as the US and the UK have increased over recent decades, the size and amount of debt for students and graduates have also increased. According to the UK’s Department of Education, total student debt has increased from about 20 million pounds in 2006 to slightly over 100 million pounds at the end of 2018. In America, student debt alone is estimated to be around 1.3 trillion dollars (U.S Census data).
Kopecky (2017) mentions how the burden of student debts restrict access to finance in the form of having less money to invest as well as finding it harder to receive a loan from banks and therefore makes it extremely hard for graduates to start their own business ventures. “A graduate with $30000 in student loans is 11% less likely to start a new business compared to a debt-free graduate” (Krishnan, 2017). In addition to that, student debt amplifies the impacts of business failure and thus starting a new risky business may seem irresponsible and illogical for fresh graduates. The stress of paying back student loans forces university graduates into the idea that working as an employee in order to ensure that they are able to receive a stable risk-free source of income to pay back loans is more attractive compared to being an entrepreneur.
Research Questions
- Do different university courses affect the intention for entrepreneurship among students?
Scholars such as A. Jimenez (2015) have only argued the effects of a high school education on entrepreneurship. He mentions that a high school education can affect entrepreneurship rates positively as high school graduates have higher average self-confidence as well as increased access to both financial and human capital. On the other hand, a high school education can also be linked to a decrease in entrepreneurship rates as high school graduates are likely to be more aware of the risks associated with entrepreneurship.
However, this seems to be the extent of research into how education affects entrepreneurship rates. Kozeniauskas’ (2017) has argued that the decrease in entrepreneurship seemed to be higher for people who achieved a higher degree in education. The decrease in entrepreneurship rates for high school graduates was only around 13% whereas the decrease for university graduates was about 35%. The difference in entrepreneurship rates for high school and university graduates is significant and research into how different university courses affect the intention for entrepreneurship among students has not been recorded and thus I believe it is crucial to answer this research question.
- Do universities such as the University of Bristol provide sufficient help for young entrepreneurs?
Universities provide great opportunities for entrepreneurship in the form of help centres and external advice for students but despite this entrepreneurship rates for university graduates are still decreasing. Answering this research question would prove extremely useful for students wanting to start the journey of entrepreneurship as well as helping universities in implementing new methods of not only promoting entrepreneurship to students through methods such as increased entrepreneurship groups, but also providing help and support.
Research Design
Ontology is concerned with what we believe constitutes reality and for this research proposal I will be adopting an objectivist view. Objectivism is an ontological position that implies that social phenomena confront us as external facts beyond our influence. I view entrepreneurship as something that is made up of physical objects such as buildings and land as well as in-material entities such as the rules and regulations as well as division of labour. As objectivism and positivism is linked, I will be taking a positivist perspective.
Positivism “is an epistemological position that advocates the application of the methods of the natural sciences to the study of social reality” (Bryman, 2001). Positivism regards reality as consisting of events that can be observed by the human senses and that science must be conducted in a method that is value free. Methodology is defined as “the theory of how research should be undertaken, including the theoretical and philosophical assumptions upon which research is based and the implications of these for the method adopted” (Saunders et al., 2016).
I will be taking a deductive approach to my research. A deductive approach is when a study starts with a theory and a hypothesis is developed. This hypothesis is then tested using data collection and analysis of the data and thus results will either prove or disprove the hypothesis. I will be using quantitative instead of qualitative research as “Quantitative research usually emphasises quantification in the collection and analysis of data. As a research strategy, it is deductivist and objectivist and incorporates a natural science model of the research process” (Bryman and Bell, 2015).
The purpose of this survey would be to research what students from the University of Bristol planned to do after graduating, show the intention for entrepreneurship amongst students studying in the University of Bristol, answer which university courses affect entrepreneurship rates the most and understand whether the University of Bristol provides sufficient support for entrepreneurs. Kruger and Casrud (1993), Crant (1996) and Kolvereid (1996) have all explored the intention of entrepreneurship in college students but none of them have explored the intention of entrepreneurship in students from universities such as the University of Bristol and this survey is an effort to fill that gap.
Firstly, the population for the survey would be all students attending the University of Bristol and I will be using a sample size of 100 students to gather data for the population. I will be using stratified random probability sampling where the population is grouped according to certain characteristics and random selections are then made from each group. Population will be grouped based on the university courses they are currently taking. In order to answer the research question proposed, survey will require participants to list down personal information such as university course, age, nationality, occupation of parents and whether they currently have a student loan.
Survey will also require participants to rate on a scale from 1-10 their intention for starting a business (10 being will definitely start a business in the future and 1 being will definitely not start a business in the future and including a ‘don’t know’ option) as well as the reasons for wanting to start a business. In order to answer whether students believe the university provides sufficient support for entrepreneurs, participants will be required to answer on a scale from 1-10 (10 being extremely supportive and 1 being not supportive at all and including a ‘don’t know’ option) whether they believe the university provides sufficient support for young entrepreneurs. Finally, looking at which university courses affect entrepreneurship the most, we must ensure that factors such as student loans and nationality are taken into account when comparing data gathered in order to ensure that we achieve an accurate result.
One of the main advantages of the survey proposed would be ease of access to participants as the survey can be easily administered to University of Bristol students in the form of handing out the surveys in areas with a high population of students (campus grounds, university library, student accommodations) as well as sending out the survey through emails and announcements. The use of stratified random probability sampling also reduces sampling error. Moreover, another advantage of the survey proposed would be that instead of asking participants whether they are satisfied with the support the university provides for entrepreneurs, they are asked to rate on a scale from 1-10 (10 being extremely supportive and helpful and 1 being not support and helpful at all). This creates allows participants to provide a more accurate answer instead of Yes/No answers which are likely to be inefficient and inaccurate.
One of the main limits of the survey would be the limited sample size due to restraints such as time. This could lead to inaccurate answers as well as a sample or selection biases. Moreover, since sample size is relatively small, intention for entrepreneurship amongst students interviewed may not be accurate when generalized for the entire population (all students in the University of Bristol). Some groups may be over-represented whereas others are under-represented. In addition to that, one of the main disadvantages of a survey would be that the lack of an incentive may cause participants to feel discouraged in providing accurate and honest answers and may instead provide answers that ensure they prevent themselves in a favourable manner. Also, since values are used to answer questions in the survey, may lead to uncertainty even if values are defined clearly.
Consideration of Ethical Issues Arising from the Research
In order to ensure that ethical issues have been dealt with, I will be using Diener and Chandall’s (1978) four main categories of ethical principles in research:
- whether there is harm to participants
- whether there is a lack of informed consent
- whether there is an invasion of privacy
- whether deception is involved.
Firstly, since the survey requires participants to provide personal information such as family size and occupation of parents, we must take into account the issue of invasion of privacy as revelation of their identity and breaking confidentiality may lead to potential harm. This is extremely important for this research as the sample size for the survey being conducted is relatively small (only 100 participants). In addition to that, extreme care needs to be taken when findings and results are being published in order to ensure that all participant’s personal information will not be leaked and used for other purposes.
One method of doing so would be ensuring participant’s basic information that is not included in the questionnaire such as participant’s name will not be included in the published findings and that information gathered from the questionnaire is safely and securely stored. Confidentiality of information provided is crucial and therefore issues relating to confidentiality of all participants will be negotiated and agreed with before research has started.
In addition to that, in order to ensure that survey participants are comfortable with providing personal information for the survey, it is crucial that participants are informed of their right for withdrawal and ensuring them that all information provided will be kept confidential and in line with the Data Protection Act. It is also important to stress the fact that participation is voluntary and that refusing to participate or withdrawing will involve no penalty.
Reflections on Limitations and Constraints
Firstly, one of the main limitations and constraints of this research proposal would be time. Having only a few months to gather information required for the survey would lead to problems such as having a relatively small sample size compared to the general population (all students in the University of Bristol) and having a large sample size is crucial when conducting quantitative research. Having a sufficient sample size is key in ensuring that all information gathered by the questionnaire is accurate and can be generalized to a larger population.
In addition to that, the constraints of time could lead to issues with sample and selection of participants. Even though a stratified random sampling method is used, there is always a chance of sampling error where some groups are over-represented and some groups are under-represented. Having a longer time frame would allow the research to ensure that there were no biases when selecting participants as well as reducing the probably of random errors. Finally, time constraints may lead to biased or one-sided arguments as only a certain number of academic papers can be read in the given time frame. Inexperience in conducting research on this topic may also lead to inaccurate data collection.
Brief Closing Summary
This research proposal is aimed at understanding which university courses affect the intention for entrepreneurship the most and whether universities such as the University of Bristol provide sufficient support for young entrepreneurs. I have provided my ontological and epistemological perspectives while explaining the research design and how I intend on collecting and analysing data gathered from the survey. I have also included limitations and restraints of my research proposal such as time which can negatively impact my research design and collection of data.
In addition to that, I have listed and reviewed the main literature provided by scholars as to why entrepreneurship has faced a decline over recent years. Based on evidence provided by other scholars as well as providing reasons backed up by the Global Entrepreneurship Monitor, I have argued that the relationship between life expectancy and the decrease in entrepreneurship rates is highly unlikely. Other factors such as university courses taken and the increase in occupational licensing are likely to play a bigger role in both the decrease in entrepreneurship over past years as well as the intention for entrepreneurship in the future.
