Research Article: 2024 Vol: 27 Issue: 4
Chempreneurs - Entrepreneurship in the Chemical Industry in Poland: A Post-COVID-19 Perspective
Sebastian Walther, Fresenius University of Applied Sciences
Stephan Haubold, Fresenius University of Applied Sciences
Renata Dobrucka, Poznań University of Economics and Business
Citation Information: Walther., S, Haubold., S & Dobrucka., R (2024). Chempreneurs - entrepreneurship in the chemical industry in poland: a post-covid-19 perspective. Journal of Entrepreneurship Education, 27(4),1-17.
Keyword
Innovation and Infrastructure, Chempreneurs, Entrepreneurs, Chemistry Students, Poland.
Introduction
The history of the chemical industry is Mayked by innovations, discoveries and industrial activities. Mayia Sklodowska Curie, for example, can be considered one of Poland’s most famous chemists due to her groundbreaking research on radioactivity earning her the nobel prize twice. Examples of Poland’s innovative strength include the founding and growth of Ciech, a chemical company with international reach and economic orientation (Wysocki, 2021).
The need for innovation is evident in view of the latest regulatory changes for all industries. The aim is to achieve climate neutrality throughout Europe by 2050 (europa commission, 2023). Both new production processes and new products are playing a key role in the significant reduction of the human carbon footprint (Confalone, 2014). Since nearly every production process includes products from the chemical industry, innovations from the chemical industry have a major influence on the entire carbon footprint of a country. To this end, the European Commission wants to support areas of the economy, companies and sectors for the transition to low-emission technologies, the creation of attractive conditions for public and private investors, facilitating access to credit and loans as well as financial support, investment in the creation of new companies, SMEs and start-ups, and investment in research and innovation. The European Union is providing a total of 1.5 trillion euros for this purpose (Europäische Kommission , 2020). Technology transfer, playing a major role in the formation of chemistry start-ups, can take place through patents, university spin-offs or, for example, company start-ups (Wolf et al ., 2021). Entrepreneurship is thus a way of promoting innovation and competitiveness in the chemical industry (Walther et al., 2023). The COVID-19 pandemic changed learning, implementation and practice in all areas of business, education, healthcare and technology. The need for independent action and initiative changed the mindset of learners, which should be considered in studies and research on their impact (Maheshwari et al., 2022). Within a change process, the way of thinking patterns can be subject to change, thus the likelihood of students starting a business may be increased by the potential loss of income and jobs (Cruz et al., 2022).
Literature Review
Entrepreneurship in Poland
Entrepreneurship plays a crucial role in fostering innovation and competitiveness in the chemical industry. Start-ups and small companies contribute to technological advances and economic growth and are therefore an essential part of the industry's ecosystem. The potential applications for chemical products and concepts are both available and necessary in light of global challenges such as human health, crop production, energy conversion and storage, safe and abundant water and climate change. For the chemical industry to survive, the gap between science and entrepreneurship must be bridged, for example through technology transfer (Sachse & Maytinez, 2016). Technology transfer can take the form of patenting, licensing or start-ups. As a means of technology transfer, entrepreneurship has attracted the attention of many different disciplines (Kirzner, 1985). With globalisation and its impact on cultural diversity, entrepreneurship has become an important area of research in its own right. Due to the belief of many authors that entrepreneurship can be learned, many studies have been conducted on the entrepreneurial intentions of university students from different disciplines, such as business administration (Abigail et al., 2022; Ajzen I. , 1991; Franke & Lüthje, 2004). Due to the specificity of STEM students in terms of their learning patterns, behaviours and self-efficacy, it is not advisable to generalise from other study programmes or cultures (Rittmayer & Beier, 2009). The present study focuses on identifying the action gap between the idea and starting a business among chemistry students in Poland.
The differences in entrepreneurial intentions of 18-64 year olds have been widely analyzed. The annual survey Global Entrepreneurship Monitor (GEM) has monitored entrepreneurial activity in more than 59 countries since 1997. These reports show the development of entrepreneurial activity in a representative cross-section of a population group for the respective year (Bosma et al., 2012; Iakovleva et al., 2011). This allows us to understand the impact of various effects. Poland shows a stable economy, which showed faster recovery effects after the Corona pandemic than other EU countries. At the same time, Poland has shown a declining TEA rate from 10.7 to 1.6 since 2016. The TEA rate is the probability of starting or running a business by 18-64 year olds. This puts Poland in the worst position of all countries analysed in 2023.
Theoretical Framework
The evaluation of entrepreneurship studies can vary depending on the research question and objective. Consequently, there are studies with different focal points. Some studies address the issue of cultural differences in entrepreneurial motivation, which can be defined by comparing countries of origin, nationalities and places of residence. The willingness to start a business can be assessed by surveying individual population groups, as in comparative studies, or by combining cross-sectional studies from different country reports into an overall survey, as in the case of the Global Entrepreneurship Monitor. The best-known models for investigating the willingness to start a business and its influencing factors include the Entrepreneurial Event Model (EEM) (Shapero, 1985) and the Theory of Planned Behaviour (TPB) (Ajzen I. ,1985). The explanatory power of the models and the elements applied can vary from country to country and from discipline to discipline (Engle, et al., 2008). The TPB is considered the most frequently cited model (Walther, et al., 2023). Depending on the methodology, both the willingness to establish a company and the reasons for the differences were analysed. For example, significantly higher start-up intentions were analysed among Greek IT students than among male study participants. A negative influence of entrepreneurial barriers, such as knowledge and skills for entrepreneurship, and internal barriers, such as time and risk, were identified as influencing factors for the general intention to start a business (Sitaridis, 2019). As a further research focus, the immediate environment of the study participants is described as a social norm or perceived social norm. Positive influences are described by a positive attitude of the environment or a positive perception of the attitude of the environment on the willingness of study participants from e.g. South Korea, Malaysia or Vietnam to start a business (Koe & Majid, 2021; Nguyen, 2020). Other demographic variables analysed in the literature include income, the respective occupation of a parent, educational background and age (Singh, 2014; Pinazo Dallenbach & Castelló Sirvent, 2023).
In this paper, the Theory of Planned Behaviour (TPB) is used as a theoretical framework to understand the psychological factors that influence entrepreneurial intentions and behaviours. The TPB comprises three key components: Attitude, Subjective Norm and Perceived Behavioural Control. We will examine these components in the context of entrepreneurship among chemistry students in Poland. The TPB model includes the intention of starting a business as a dependent variable, and the mediators attitude, subjective norm, and perceived behavioural control as factors (Ajzen 1991, p. 182). For this study, the model was extended to include the factors such as start-up knowledge, perceived educational support, perceived support from the university/research institution and perceived career opportunities. The adapted model can be seen in Figure 1.
Figure 1 Adapted Research Model According to the Theory of Planned Behaviour
Founding Knowledge
Founding knowledge refers to a person’s understanding of the fundamental aspects of founding and running a company. This is a decisive factor for entrepreneurial intentions based on basic knowledge of business management and entrepreneurship. In the context of educational programmes, imparting entrepreneurial knowledge can be a suitable method for increasing the number of potential start-ups. Start-up knowledge can influence potential founders in two areas, on the one hand in the corresponding attitude and on the other via the general knowledge of business start-ups through entrepreneurship courses. The necessary knowledge for business start-ups is not taught as part of a traditional chemistry degree programme, which can deter interested students from potentially starting a business due to the lack of knowledge and preparation. For example, respondents who would like to start their own business are aware that their technical and business knowledge is not sufficient (Teixeira, 2008). A general dependency of entrepreneurship on attainable factors is described in other studies and models (Kolvereid & Moen, 1997). Entrepreneurship education has already been investigated among Polish schoolchildren and showed a positive effect on their willingness to start a business (Packham et al., 2010). Based on the representative survey by Gem, Poland shows a very undervalued assessment of foundation knowledge (Doan, 2022). This effect cannot be confirmed by the comparative study of chemistry students in Germany and Poland, in which sometimes Germany and sometimes Poland show higher ratings with significant differences (Walther et al., 2023).
Based on these described correlations, we hypothesise that general knowledge about business start-ups has a positive influence on the willingness of chemistry students in Poland to start a business (H1).
Perceived Educational Support (PES) & Perceived Support of the University (PSU)
The role of education in promoting entrepreneurship cannot be underestimated. On the one hand, future experts are needed to impart knowledge and, on the other hand, there is a need for workers in industry. In this regard, the Polish government has already tried to increase the number of first-year students in STEM subjects through funding and support (FUNDACJA PAP, 2010). Perceived educational support and university support can have a significant impact on the likelihood of individuals pursuing entrepreneurial ventures. In this regard, the university can argue, for example, through cognitive support (Trivedi, 2016). At the same time, the university can also take measures to increase or raise awareness of entrepreneurship as a career option. This can increase self-confidence in starting one’s own business (Gorman et al., 1997). The studies show different results, in some cases significant influences are described (Schwarz et al., 2009) in others not (Trivedi, 2016). A study of students in Saudi Arabia in 2022 found a strong moderating relationship between perceived university support and Goal Setting, Environment Structuring, Task Strategies, Self-evaluation, and students’ entrepreneurial intentions which becomes higher when students perceive high university educational entrepreneurship support (Mahgoub et al., 2023). The comparison of Germany and Poland revealed significant differences in Perceived Educational Support (PES) & Perceived Support of the University (PSU) with higher ratings in Germany.
Therefore, we hypothesise that university entrepreneurship education has a positive influence on the willingness of chemistry students in Poland to start a business (H2).
Subjective Norm
Within the framework of the TPB, the subjective norm is described as the second predictor. This defines the perceived social pressure triggered by the family, and the close environment of persons and peers. The direction and effect depends on the opinion of the reference persons (Ajzen 1991, p. 188; cf. Ajzen 1985, p. 14). However, students’ perceptions can be changed or influenced (Nanda & Sørensen, 2008). The literature points to different socialisations among the sexes, so that women are socialised differently and therefore perceive opportunities differently (DeTienne, 2007). Different assessments were also found among male and female chemistry students in Poland and Germany (Walther et al., 2023). This means that women indicated less of a rigid social norm for a possible business start-up. At the same time, scientific studies show that regions with higher social acceptance also have more entrepreneurial activities (Kibler, 2013). For example, among Polish students, no significant influence of the subjective norm after the Covid period on entrepreneurial intention could be proven, which, however, was justified with the province of Podlaskie as the region of the survey, which is not known for innovative entrepreneurial activities (Kobylinska, 2022).
We therefore hypothesise that the acquaintance with a company founder in the students’ circle of acquaintances has a positive influence on the willingness of chemistry students in Poland to start a company (H3).
Perceived Career Options
Chemists have a variety of career options, including traditional employment in industry, public service, academia or entrepreneurship. The perceived career option is the personal attitude towards a career path. This can be based on individual beliefs and experiences (Roy et al., 2017). In this context, a deeper understanding of personal career ambitions and desired work activity can be developed based on individual analysis and consideration in relation to one's own interests, values and experiences (Zikic & Klehe, 2006). When comparing perceived career options, individuals choose the option with the greatest personal benefit based on attributes such as risk taking, workload, financial success or recognition (Roy et al., 2017). Perceptions of one’s own skills and abilities play a crucial role (Douglas & Shepherd, 2002). As a result, individuals with confidence in a career option may feel that their skills are not sufficient in some respects to succeed which is tantamount to excluding that career option. The initial economic situation can also influence career options, for example, starting a business is more likely if there are few vacancies in existing companies (Dyer Jr., 1995).Due to the quick access to jobs with perceived career opportunities in Poland, it can be assumed that starting a business as a career option is less likely (Zajac et al., 2023).
We therefore hypothesise that the perceived career opportunities of chemistry students in Poland have a negative influence on their willingness to start a business (H4).
Motives and Barriers
Understanding what motivates people to start a business is as important as understanding the barriers to doing so. Previous comparative studies between countries and occupational groups show clear differences (Doanh, 2018; Giacomin, et al., 2011). A distinction can be made between extrinsic factors, which mainly relate to economic activities, and intrinsic factors, such as some personality-related characteristics. The study by (Walther et al., 2023), which compares different studies, found that “implementing my own idea”, “being independent” and “creating something of my own” are the strongest motivating factors, while “lack of start-up capital2”, “too high risk” and “lack of knowledge” are the biggest obstacles to entrepreneurial activities. The comparative study of German and Polish chemistry students revealed that the strongest motives were “to create something on my own”, “the opportunity to be financially independent”, and “the opportunity to realise my own ideas” for the Polish participants. While "the current economic situation", "a lack of initial capital" and "a lack of knowledge of the Mayket" were the strongest barriers for the chemistry students from Poland (Walther et al., 2023). Other comparative studies point to the significant differences in intentions and perceptions of motives or barriers due to cultural differences between nations (Pruett et al., 2009; Giacomin, et al., 2011). Wach & Bilan suggest that Polish students' entrepreneurial intention is significantly positively influenced by the Polish culture of negative barriers and experiences with a family business in their own household. Based on these results, we assume that there is a connection between high perceptions of motives and barriers and the willingness of chemistry students to start a business (Boissin et al., 2009; Confalone, 2014).
We therefore hypothesise that this effect is positive for motives (H5) and negative for barriers (H6).
Methodology
This study is part of a comparative study of German and Polish chemistry students that examines innovation-oriented technology transfer from the students’ perspective. Due to time and cost constraints, a longitudinal design was chosen for our study. The chosen method was a survey with one measurement point (August 2022 - January 2023) to collect prospective and current data using an online questionnaire.
Additional questions were added to the questionnaire used in this article. The questionnaire was translated into English, French, Spanish and Polish by specialised staff and then checked for loss of meaning. The target group for the survey was students from the departments of chemistry as well as related fields (biochemistry, analytics, industrial chemistry, process engineering, industrial biology and food chemistry) who were contacted by mail, personally in lectures or via online social media networks like Instagram.
Survey
This study is part of a comparative study of German and Polish chemistry students that examines innovation-oriented technology transfer from the students’ perspective. Due to time and cost constraints, a longitudinal design was chosen for our study. The method chosen was a survey with one measurement point (August 2022 - January 2023) to collect prospective and current data using an online questionnaire. Additional questions were added to the questionnaire used in this article. The questionnaire was translated into English, French, Spanish and Polish by specialised staff and then checked for loss of meaning. The target group for the survey was students from the departments of chemistry as well as related fields (biochemistry, analytics, industrial chemistry, process engineering, industrial biology and food chemistry) who were contacted by mail, personally in lectures or via online social media networks like Instagram.
Questions
The questionnaire used in this study is composed of questions from different studies. The questions are divided into demographic factors, the probability of founding or career intentions and the assumed influencing factors from the TBP with supplemented questions. The questions were asked in the fixed order of demographic questions, external influencing factors, start-up probability and personal influencing factors. After the demographic questions on gender, migration, nationality and age, participants were excluded due to their student status in order to obtain the desired data. Subsequently, study-relevant characteristics such as place of study, field of study, intended degree, total duration of study, type of employment or the presence of founders in the environment were recorded and questions were asked to determine the latent constructs. For this, questions from different studies were used, which were adapted to a 6-point Likert scale to force selection. Absolute ignorance (1) to comprehensive knowledge (6) for questions on basic knowledge, or I don't know (0), don't agree at all (1) to completely agree (6) for the others. The probability of founding a company was asked through two different types of questions, on the one hand the probability of founding a company after graduation ranged from very unlikely (1) to very likely (6) and on the other hand the career intentions with the options public service, employment and founding a company. Based on career intentions, the entrepreneurial intentions (TEA rate) for the students are determined by percentage calculation. An overview with the question categories used, the number of questions, the presence of the answer option "I don't know" as well as the question source can be found in Table 1.
| Table 1 Overview of Applied Study Questions with Sources, Number and Additions | ||||
| Question Categories | Number Of Questions | Answer option “I don’t know” | Question source | Addition of own questions |
| Foundation knowledge | 3 | no | (Cook, Heath, & Thompson) | no |
| Perceived educational support (PES) & Perceived Support of the university (PSU) | 10 | yes | (Roy, Akhtar, & Das) | yes |
| subjective norm (SN) | 2 | no | (Saeed, Yousafzai, Yani-De-Soriano, & Muffatto) | no |
| Founding intention | 2 | no | (Saeed, Yousafzai, Yani-De-Soriano, & Muffatto) | no |
| Question Categories | Number Of Questions | Answer option “I don’t know” | Question source | Addition of own questions |
| Perceived Career options (WCO) | 6 | yes | (Cook, Heath, & Thompson) | no |
| Perceived Behavioural control (PBC) | 9 | yes | (Zapkau, Schwens, Steinmetz, & Kabst) | no |
| Self-assessment for the foundation (SF) | 3 | yes | (Krueger, Reilly, & Carsrud) | no |
| Motives for Starting a Business | 17 | yes | (Pruett, Shinnar, Toney, Llopis, & Fox, 2009), (Solesvik) | yes |
| Barriers to Starting a Business | 19 | yes | (Pruett, Shinnar, Toney, Llopis, & Fox, 2009), (Solesvik) | yes |
Participants
A total of 4,367 people and 120 professors or student representatives were contacted. In February 2023, we received completed questionnaires from 1,287 participants, a response rate of 29.4 %, which is acceptable compared to other web-based studies (Cook et al, 2000). Before conducting our statistical analyses, we excluded 320 participants due to incomplete data. We also excluded participants who reported that they were not currently a student (n = 135), or belonged to another field (such as teaching or electrical engineering), or were studying in another country (n = 21). The final sample thus consisted of 811 students, 498 from Germany and 313 from Poland. The average time spent in the questionnaire was 9.25 minutes. A sumMayy of the distribution of study participants can be found in Table 2.
| Table 2 Summayy of the Study Participants | ||
| Types | Number (n) | |
| total | 1,287 | |
| exluded | 476 | |
| included | 811 | |
| Poland | 313 | |
| SUB groups | ||
| Gender | Male | 88 |
| Female | 219 | |
| Migration Background | yes | 64 |
| no | 249 | |
| desired degree | Bachelor | 224 |
| Master | 64 | |
| income | no income | 187 |
| Part time job | 109 | |
| Founder-approved | yes | 196 |
| no | 117 | |
The students from Germany were on average 22.8 years old (SD = 3.42, range 17-39) and not homogeneously distributed between men (27.5 %) and women (69.9 %). Almost a quarter (21.9%) had an immigrant background. Most participants (72.2%) are enrolled in a Bachelor’s degree programme (20.9% in a Master's degree programme, 6.9% in a doctoral programme). 59.9 % of students (n = 209) have no income from employment, while 4.3 % (n = 15) report full-time employment. Most students have a founder in their circle of acquaintances (n = 213, 61.0 %).
Statistical analysis
Statistical analysis was carried using IBM SPSS Statistics version 28.0.1. The data was tested for normal distribution using Shapiro-Wilk tests. Not all variables in the data set have a normal distribution and some variables have an ordinal scaling. The (Fisher & Yates, 1938) logistic ordinal model is used to study the effect of continuous and categorical variables on a dependent variable (Reed & Wu, 2013). First, an exploratory factor analysis (EFA) is carried out with the maximum likelihood extrusion method. Variables with a factor loading of less than 0.5 are excluded for further calculations. As a further parameter, the reliability measure Cronbach’s Alpha (CA) is used, which is considered reliable if it exceeds the threshold value of 0.7 (Nunnally, 1978). This allows 12 variable factors to be generated from 69 variables.
To prepare an ordinal logistic regression (OLR), the results are coded as Y = 1 or Y = 0, where the result either occurs (1) or does not occur (0). Further, OLR is performed as an analysis on the factor variables. Thus, OLR is used to determine the effect size (Exp(B)) as 95 % Wald confidence interval, predict effects, detect trends and help predict the relationship between an endogenous variable at the ordinal level and two or more categorical or continuous exogenous variables. Chi-square test and goodness-of-fit according to Person and Deviance as well as pseudo R-squared according to Nagelkerke and Cox I Snell are given as further parameters for the OLR.
The significance level was defined as 5 %. The calculation of the probability of founding a company is based on the percentage of participants who selected founding a company as a career option. The results are presented as a table showing the factor, country, number of “I don't know” statements, proportion of “I don't know” statements, sample size (n), mean, median, Wald chi-square and p-value (p).
Results
Entrepreneurial Intentions
The readiness of chemistry students in Germany to start a business is shown for all subgroups in Figure 2.
Figure 2 Boxplot Fort He Founding Intentions Oft He (Sub) Groups of Students
As Figure 2 shows, the intention of chemistry students in Poland to start a business is rather low across all groups, with median and mean values around 2, which indicates a low probability of starting a business. Only the SUB groups of students without social capital and participants in a Master’s degree programme show a lower mean, median and third quartile.
After selecting variables with a factor loading of at least 0.5 and a Cronbach’s alpha (CA) of at least 0.7, the factor analysis resulted in 13 factor variables. The further course of the ordinal regression was thus limited to the variable factors (Table 3):
| Table 3 Questions in the Variable Factors | |
| Variable factors | Questions from survey |
| foundation knowledge | To what extent do you know about the tasks involved in setting up a business? |
| To what extent can you distinguish between a “good” and a “bad” start-up idea? | |
| Do you know of any funding organisations that can help you with your start-up? | |
| Education support 1 | My college/university offers lectures on the topic of start-up/entrepreneurship. |
| My college/university offers projects on the topic of start-up/entrepreneurship. | |
| My college/ university hosts conferences /workshops on startup/entrepreneurship. | |
| My college/university puts students interested in starting a business in touch with each other. | |
| My college/university has a start-up center. | |
| My university has clear rules for the transfer of ideas from research to a start-up company. | |
| Education support 2 | My college/university motivates students to start a new business. |
| My college/university provides students with ideas for starting a new business. | |
| I am aware of foundation events outside my university for people interested in foundation their own business. | |
| Subjective norm | People I care about expect me to start a business after I graduate. |
| People who are important to me think that I should start a business after I graduate. | |
| Perceived career options | The choice between the different career options is so complicated that I can't decide. |
| The more I try to find out about different career options, the more confused I get. | |
| I think a lot about choosing the right career. | |
| Motives 1 | earn more money than through wage labour |
| to work in a varied profession | |
| the building of personal wealth | |
| to have more free time | |
| attainment of a high social status | |
| Variable factors | Questions from survey |
| Motives 2 | the continuation of a family tradition |
| to contribute to the economy | |
| contribute to regional economic development | |
| Motives 3 | to be at the head of an organisation |
| the creation of jobs | |
| to lead people | |
| Motives 4 | the opportunity to realize my own ideas |
| to create something on my own | |
| my personal independence | |
| Barriers 1 | lack of experience of accounting |
| the lack of guidance | |
| lack of support in setting up a business | |
| paperwork and bureaucracy when setting up | |
| lack of support from people around me. | |
| Barriers 2 | excessive risk |
| the lack of initial capital | |
| my own fear of failure | |
| lack of experience in management | |
| too much work in setting up a business | |
| Barriers 3 | the lack of credit for start-ups |
| the applicable state laws (rules and regulations) | |
| the fiscal charges (taxes, court fees, etc.) | |
| Barriers 4 | a of knowledge in the business world |
| a lack of knowledge of the Mayket | |
The results for the ordinal regression with the 12 factor variables and the 8 subgroups can be found in Table 4.
| Table 4 The Ordinal Regression Results - Contrast Ratios | |||||||
| Parameters | Exp(B) | 95 % Wald confidence Interval | Hypothesis test | ||||
| Lower | Upper | Wald chi-square | p | ||||
| SUB-groups | Gender | Male | 1.41 | 0.84 | 2.35 | 1.7 | 0.192 |
| Female | 1 | ||||||
| Social capital | Social capital | 1.44 | 0.88 | 2.36 | 2.15 | 0.143 | |
| No social capital | 1 | ||||||
| Parameters | Exp(B) | 95 % Wald confidence Interval | Hypothesis test | ||||
| Lower | Upper | Wald chi-square | p | ||||
| SUB-groups | Immigration Background | immigration background | 1.05 | 0.58 | 1.91 | 0.03 | 0.864 |
| no immigration background | 1 | ||||||
| Study Programme | Bachelor | 1.64 | 0.95 | 2.83 | 3.19 | 0.074 | |
| Master | 1 | ||||||
| Income | No income | 0.94 | 0.58 | 1.51 | 0.06 | 0.8 | |
| Part time job | 1 | ||||||
| Factor variables | Foundation knowledge | 1.28 | 1.13 | 1.44 | 14.86 | < 0.001 | |
| Education support 1 | 1.02 | 0.98 | 1.06 | 0.91 | 0.341 | ||
| Education support 2 | 1.03 | 0.96 | 1.11 | 0.78 | 0.376 | ||
| Subjective norm | 1.9 | 1.56 | 2.32 | 39.82 | < 0.001 | ||
| Perceived career options | 1.07 | 0.98 | 1.17 | 2.1 | 0.147 | ||
| Motives 1 | 1.13 | 1.07 | 1.19 | 18.51 | < 0.001 | ||
| Motives 2 | 0.94 | 0.87 | 1.01 | 2.54 | 0.111 | ||
| Motives 3 | 1 | 0.91 | 1.1 | 0 | 0.945 | ||
| Motives 4 | 0.99 | 0.88 | 1.11 | 0.02 | 0.882 | ||
| Barriers 1 | 1.03 | 0.94 | 1.13 | 0.47 | 0.493 | ||
| Barriers 2 | 0.98 | 0.91 | 1.06 | 0.34 | 0.56 | ||
| Barriers 3 | 1.06 | 0.98 | 1.15 | 1.96 | 0.162 | ||
| Barriers 4 | 0.9 | 0.79 | 1.02 | 2.77 | 0.096 | ||
Among the subgroups, only the comparison between Bachelor’s and Master’s students shows a significant difference, which was already shown in the boxplot in Figure 2. It can therefore be assumed that chemistry students in Poland are more likely to start a business when they are still at the beginning of their academic career. Our survey thus confirms the results of previous surveys of other students (Kanama, 2021).
The factor variables show a significant influence in the subjective norm, foundation knowledge and motives 1. The subjective norm thus confirms the influence of the students’ immediate environment on their willingness to start a business (Nanda & Sørensen, 2008; Kautonen et al., 2011). In the results, the subjective norm is the factor with the strongest effect (1.90), which shows a direct correlation between the start-up behaviour of students and the attitude of their environment. Analogous to another study, no direct significant influence of the subjective norm was found, only an indirect influence (Kobylinska, 2022), which cannot be explained by the location of the universities.
The positive influence of start-up knowledge confirms the research (Doan, 2022). It can therefore be assumed that chemistry students do not differ in this respect from other students such as business administration students. The effect size shows a moderate effect of 1.28. It makes sense here to specifically strengthen start-up knowledge and identify SUB groups with deficiencies as in the gender comparative study by (Walther et al., 2023).
Motive 1 from the factor variables stands for “the opportunity to be financially independent”, “to improve my quality of life”, “to earn more money than through wage labour”, “to work in a varied profession”, “to build up personal wealth”, “to have more free time” and “to achieve a high social status”. The direct influence of these variables points to the desire for independence, freedom and fulfilment through something of one’s own. These driving factors for starting a business have already been demonstrated by Walther et al.,(2023) and Pruett (2009).
Male and female students in Poland show no significant difference in their start-up behaviour, which can be attributed to a high degree of equality (DeTienne, 2007). At the same time, additional analysis is required to further clarify the non-significant effect, e.g. by comparing the genders individually using an ANOVA analysis (Walther et al., 2023). This reveals fundamental differences in the assessment of genders in Poland. These should be taken into account when implementing any processes and changes in education.
Table 5 sumMayizes the key figures for the model used.
| Table 5 Statistical Key Figures for the Ordinal Regression Performed in the Applied Model | ||||||
| Test | Model | -2 Log Likelhood | Chi-Square | df | sig | Pseudo R-square |
| Test of Parallel Lines | Null Hypotheses | 758.548 | ||||
| General | 748.548b | 12.018 | 72 | 1 | ||
| Model fitting information | Intercept only | 920.561 | ||||
| Final | 758.566 | 166.995 | 18 | 0 | ||
| Goodness-of-Fit | Pearson | 1310.759 | 1347 | 0.755 | ||
| Deviance | 758.566 | 1347 | 1 | |||
| Pseudo R-squared | Cox / Snell | 0.446 | ||||
| Nagelkerke | 0.462 | |||||
| McFadden | 0.176 | |||||
As Table 3 shows, the model applied fits the data well, which is confirmed by the confounded measures used. The -2 log-likelihood, the chi-square tests and the pseudo R-squared measures show that the model explains the variation in the data well and has a good model fit. The pseudo R-squared values indicate that the independent variables can explain about 44.6 % to 46.2 % of the variance in entrepreneurial intentions. The test for parallel lines shows that the assumption of parallel regression effects is fulfilled.
The results can be used to confirm hypotheses 1 “general knowledge about business start-ups has a positive influence on the willingness of chemistry students in Poland to start a business”, H3 “the acquaintance with a company founder in the students’ circle of acquaintances has a positive influence on the willingness of chemistry students in Poland to start a company” and H5 “A positive correlation between a high perception of motives and the willingness of chemistry students to start a business”. Hypothesis 2 “university entrepreneurship education has a positive influence on the willingness of chemistry students in Poland to start a business”, hypothesis 4 “the perceived career opportunities of chemistry students in Poland have a negative influence on their willingness to start a business” and hypothesis 6 “A negative correlation between a high perception of barriers and the willingness of chemistry students to start a business” were rejected.
Discussion
The distribution across the subgroups shows that the willingness to start a business is lower among participants in a Master’s degree programme. Possible effects such as good career prospects for chemists may have an influence here (Zajac et al., 2023). At the same time, the gender subgroups show an increased willingness to start a business among women and chemistry students with founders in their circle of acquaintances, even if this is not significant. This indicates, on the one hand, cultural influences in relation to nationalities (Giacomin, et al., 2011) and, on the other hand, positive experiences from the students' immediate environment.
The results of the factor groups clearly show a connection between the willingness of chemistry students to start a business and their start-up knowledge, their perception of the subjective norm and their motives for starting a business. We therefore recommend the establishment of at least one compulsory course on entrepreneurship. In this way, knowledge of how start-ups work can be increased and barriers broken down. One possible approach is to invite founders to speak to the students as part of the university curriculum. This would allow students to build a network with founders and at the same time benefit from positive experiences. This would be in line with the findings of (Abigail et al., 2022). Critical authors state that the greatest learning success is achieved through practical application (Gendron, 2004). The factors with a positive effect on the willingness of chemistry students in Poland to set up a company can be a good starting point for a successful technology transfer after the Covid pandemic. The impact of EE on Polish chemistry students should be investigated directly and examined in detail. Our survey thus confirms the results of previous surveys of other students Wolf et al., 2021.
This study merely serves to provide an initial overview of the willingness of Polish chemistry students to start a business and the factors influencing this. As this is not a representative study but a random sample, only tendencies can be explained. For future research, we therefore recommend a larger number of participants in addition to representative studies in order to be able to carry out effect analyses for other SUB groups. Future analyses can explain how differently the different SUB groups of chemistry students see the influence of the various factors on the start-up intentions of chemistry students or classify them in order to be able to derive more targeted measures.
References
Abigail, J. G., Jeslin, C. J., Vijayarangan, P. B., & Rakhi, Y. (2022). Chemistry Innovations and Ideas from the Classroom to the Real World: The Students’ Perspective on Becoming a Chemistry Entrepreneur. Journal of Chemical Education, 1556-1562.
Ajzen, I. (1985). From intentions to actions: A theory of planned behavior. Action control, 11-39.
Ajzen, I. (1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes , 179 - 211.
Indexed at, Google Scholar, Cross Ref
Autio, E., Keeley, R., Klofsten, M., Parker, G., & Hay, M. (2001). Entrepreneurial intent among students in Scandinavia and in the USA. Enterprise and Innovation Management Studies, 2 (2), 145-160.
Indexed at, Google Scholar, Cross Ref
Boissin, J. P., Branchet, B., Emin, S., & Herbert, J. I. (2009). Students and entrepreneurship: a comparative study of France and the United States. Journal of Small Business & Entrepreneurship, 22(2), 101-122.
Indexed at, Google Scholar, Cross Ref
Bosma, N., Wennekers, S., & Amoros, J. (2012). Global Entrepreneurship Monitor 2011 extended report: Entrepreneurs and entrepreneurial employees across the globe. Babson Park, MA: Babson College.
Boyd, N. G., & Vozikis, G. S. (1994). The influence of self-efficacy on the development of entrepreneurial intentions and actions. Entrepreneurship theory and practice, 18(4), 63-77.
Indexed at, Google Scholar, Cross Ref
Confalone, P. N. (2014). Innovation and entrepreneurship in the chemical enterprise. In Careers, Entrepreneurship, and Diversity: Challenges and Opportunities in the Global Chemistry Enterprise (pp. 163-171). American Chemical Society.
Cook, C., Heath, F., & Thompson, R. L. (2000). A meta-analysis of response rates in web-or internet-based surveys. Educational and psychological measurement, 60(6), 821-836.
Indexed at, Google Scholar, Cross Ref
Cruz, P. D. A., Covarrubias, L. P. C., & Pérez, P. A. (2022). The Effect of Resilience on Entrepreneurial Intention in Higher Education Students in a Post-Covid Stage 19. Journal of Higher Education Theory and Practice, 22(18), 6-20.
DeTienne, D. R., & Chandler, G. N. (2007). The role of gender in opportunity identification. Entrepreneurship theory and practice, 31(3), 365-386.
Doan, K. H. (2022). The differences in the impact of entrepreneurship education on entrepreneurial knowledge: a cross-country analysis. Management & Marketing, 17(1), 73-97.
Indexed at, Google Scholar, Cross Ref
Doanh, D. C. (2018). Barriers to Entrepreneurial Intention among Vietnamese and Polish Students: A Cross-Country Comparison. In J. Marszalek-Kawa, & A. Zakoscielna, The Diversity of Asia in the Issues of Culture, Religion and Ethics (pp. 153 - 176). National Economics University, Hanoi, Vietnam.
Douglas, E. J., & Shepherd, D. A. (2002). Self-Employment as a Career Choice: Attitudes, Entrepreneurial Intentions, and Utility Maximization. Entrepreneurship Theory and Practice.
Indexed at, Google Scholar, Cross Ref
Dyer Jr., W. G. (1995). Toward a Theory of Entrepreneurial Careers. Entrepreneurship Theory and Practice.
Indexed at, Google Scholar, Cross Ref
Engle, R. L., Dimitriadi, N., Gacidia, J. V., Schlaegel, C., Delanoe, S., Alvarado, I., Wolff, B. (2008). A twelve-country evaluation of Ajzen's model of planned behavior. Internation Journal of Entrepreneurial Behaviour & Research, 36 - 57.
Europa commission. (2023). Der europäische Grüne Deal.
Europäische Kommission . (2020). european reen deal.
Fisher, R. A., & Yates, F. (1938). Statistical Tables for Biological, Agricultural, and Medical Research. Michigan: University of Michigan.
Franke, N., & Lüthje, C. (2004). Entrepreneurial intentions of business students benchmarking study. International Journal of Technology and Management, 269–288.
Indexed at, Google Scholar, Cross Ref
FUNDACJA PAP. (2010). Kudrycka: Polska potrzebuje wiecej absolwentów kierunków technicznych.
GEM (Global Entrepreneurship Monitor). (2023). Global Entrepreneurship Monitor 2022/2023 Global Report: Adapting to a “New Normal”. London: GEM.
Gendron, B. (2004). Why Emotional Capital Ma tters in Education and in Labour? Toward an Optimal Exploitation of Human Capital and Knowledge Management. In Les Cahiers de la Maison des Sciences Economiques , série rouge, n° 113. Paris: iversité Panthéon-Sorbonne.
Giacomin, O., Janssen, F., Pruett, M., Shinnar, R. S., Llopis, F., & Toney, B. (2011). Entrepreneurial intentions, motivations and barriers: Differences among American, Asian and European students. International Entrepreneurship and Management Journal .
Gorman, G., Hanlon, D., & King, W. (1997). Some Research Perspectives on Entrepreneurship Education, Enterprise Education and Education for Small Business Management: A Ten-Year Literature Review. International Small Business Journal: Researching Entrepreneurship, 3.
Indexed at, Google Scholar, Cross Ref
Iakovleva, T., Kolvereid, L., Stephan, U., & ., .. (2011). Entrepreneurial intentions in developing and developed countries. Education & Training, 353 - 370.
Indexed at, Google Scholar, Cross Ref
Kanama, D. (2021). A comparative study of the entrepreneurial motivation of undergraduate and graduate students in Japan. Industry and Higher Education.
Indexed at, Google Scholar, Cross Ref
Kautonen, T., Luoto, S., & Tornikoski, E. T. (2011). Influence of work history on entrepreneurial intentions in ‘prime age’ and ‘third age’: A preliminary study. International Small Business Journal: Researching Entrepreneurship, 6.
Kibler, E. (2013). Formation of Entrepreneurial Intentions in a Regional Context. Entrepreneurship and Regional Development, 293-323.
Indexed at, Google Scholar, Cross Ref
Kirzner, I. (1985). Discovery and capitalist process. University of Chicago Press.
Kobylinska, U. (2022). Attitudes, subjective norms, and perceived control versus contextual factors influencing the entrepreneurial intentions of students from Poland. WSEAS TRANSACTIONS on BUSINESS and ECONOMICS, 94-106.
Koe, W.-L., & Majid, I. A. (2021). Socio-Cultural Factors and Intention towards Sustainable Entrepreneurship. Eurasian Journal of Business and Economics, pp. 145-156.
Kolvereid, L., & Moen, Ø. (1997). Entrepreneurship among business graduates: Does a major in entrepreneurship make a difference? Journal of European Industrial Training, 154 - 160.
Indexed at, Google Scholar, Cross Ref
Maheshwari, G., Kha, K., & Arokiasamy, A. (2022). Factors affecting students’ entrepreneurial intentions: a systematic review (2005–2022) for future directions in theory and practice. Management Review Quarterly.
Mahgoub, I. G., Elshamly, A., & Elsayed, A. M. (2023). The moderating role of perceived university entrepreneurship support on the relationship between online self-regulated learning and Saudi students' entrepreneurial intentions. Journal of Entrepreneurship Education, 1-20.
Nanda, R., & Sørensen, J. B. (2008). Peer Effects and Entrepreneurship. Harvard Business School Entrepreneurial Management Working Paper No. 08-051, 1-25.
Nguyen, T. T. (2020). Impact of entrepreneurship environmental support factors to university students’ entrepreneurship self-efficacy. Management Science Letters, pp. 1321-1328.
Indexed at, Google Scholar, Cross Ref
Nobel Prize Outreach. (2023). Search results for 'marie curie'.
Nunnally, J. C. (1978). Psychometric Theory. New York: Mcgraw-Hill College.
Packham, G., Jones, P., Miller, C., Pickernell, D., & Brychan, T. (2010). Attitudes towards entrepreneurship education: A comparative analysis. Education + Training, 568 - 586.
Indexed at, Google Scholar, Cross Ref
Pinazo Dallenbach, P., & Castelló Sirvent, F. (2023). Gender, Perceived Insecurity, Corruption Perception, Subjective Norm, and Household Income: A Configurational Approach to Entrepreneurial Intention. Journal of the Knowledge Economy.
Pruett, M., Shinnar, R., Toney, B., Llopis, F., & Fox, J. (2009). Explaining entrepreneurial intentions of university students: a cross-cultural study, Ivol.15, no.6, pp. International Journal of Entrepreneurial Behavior & Research, 571 - 594.
Indexed at, Google Scholar, Cross Ref
Reed, P., & Wu, Y. (2013). Logistic Regression for Risk Factor Modelling in Stuttering Research. Journal of Fluency Disorders, 88-101.
Indexed at, Google Scholar, Cross Ref
Rittmayer, M. A., & Beier, M. E. (2009). Self-Efficacy in STEM . In B. Bogue, & E. Cady, Applying Research to Practice.
Roy, R., Akhtar, F., & Das, N. (2017). Entrepreneurial intention among science & technology students in India: extending the theory of planned behavior. International Entrepreneurship and Management Journal 13 (4), 1013-1041.
Sachse, A., & Martinez, J. G. (2016). A Brief Guide for the Chemistry Entrepreneur. In Chemistry without Borders: Careers, Research, and Entrepreneurship. ACS Publications, 91-107.
Schwarz, E., Wdowiak, M., Almer-Jarz, D., & Breitenecker, R. (2009). The effects of attitudes and perceived environment conditions on students’ entrepreneurial intent. Education + Training, 51(1),, 272-291.
Shapero, A. (1985). The entrepreneurial event. In C. A. Kent, The Environment for Entrepreneurship. Lexington.
Singh, I. (2014). Role of Demographic Variables in the Formation of Entrepreneurial Intention. Journal of Business and Management, pp. 20-25.
Sitaridis, I. K. (2019). Entrepreneurship as a Career Option for Information Technology Students: Critical Barriers and the Role of Motivation. Journal of the Knowledge Economy, pp. 113-1167.
Teixeira, A. A. (2008). Entrepreneurial potential in chemistry and pharmacy. Results froma large survey. Journal of Business Chemistry, pp. 48-63.
Trivedi, J. (2016). Factors Determining the Acceptance of E Wallets. International Journal of Applied Marketing and Management., 1(2), 42-53.
Walther, S., Dobrucka, R., & Haubold, S. (2023). A review on influence factors promoting or inhibiting the transfer of research from universities into start ups. , journal of business chemistry, 2023, 31-45.
Walther, S., Haubold, S., & Dobrucka, R. (2023 hoffentlich). female Chempreneurs: Differences in motivations and barriers of students depending on gender and the impact on entrepreneurship - a comparative study of Polish and German Students. Gibts noch net, X-Y.
Walther, S., Haubold, S., Zieleniewicz, A., & Dobrucka, R. (2023). Chempreneurs: Understanding Motivations, Barriers and Intentions in two selected European countries. Procedia Computer Science.
Indexed at, Google Scholar, Cross Ref
Wolf, V., Dobrucka, R., Prezkop, R., & Haubold, S. (2021 ). The SOCI Strategy as a Method to Meet the Innovation Challenges of COVID-19. International Journal of Industrial and Manufacturing Engineering, pp. Vol:15, No:5, 567 - 571.
Wolf, V., Dobrucka, R., Przekop, R., & Haubold, S. (2021). Innovation strategies in the context of the paradigm of the five dimensions of innovation strategy. Scientific Journal of Logistics , S. 205-211.
Indexed at, Google Scholar, Cross Ref
Wolf, V., Dobrucka, R., Przekop, R., & Haubold, S. (2021). PANDA as a startup-orientated cooperative innovation strategy for the chemical and pharmaceutical industry. Journal of Management and Industrial Integration and Management.
Indexed at, Google Scholar, Cross Ref
Wysocki, J. (2021). Innovative Green Initiatives in the Manufacturing SME Sector in Poland . Sustainability 13, no. 4.
Indexed at, Google Scholar, Cross Ref
Zajac, T. Z., Zóltak, T., Bozykowski, M., & Jasinski, M. (2023). All that glitters is not gold—Mixed early labour market outcomes of STEM graduates in Poland. European Journal of Education, 477-497.
Indexed at, Google Scholar, Cross Ref
Zikic, J., & Klehe, U.-C. (2006). Job loss as a blessing in disguise: The role of career exploration and career planning in predicting reemployment quality. Journal of Vocational Behavior, 69(3), 391-409.
Indexed at, Google Scholar, Cross Ref
Received: 1-May-2024, Manuscript No. AJEE-24-14867; Editor assigned: 3-May-2024, PreQC No. AJEE-24-14867(PQ); Reviewed: 17-May-2024, QC No. AJEE-24-14867; Revised: 21-May-2024, Manuscript No. AJEE-24-14867(R); Published: 28-May-2024