African S&T Professionals Trained in Chinese Universities: Orientations towards Entrepreneurship

Abstract

Entrepreneurship has emerged as an important career option in several developing countries, particularly in Africa. Consequently, entrepreneurship education and training has been sought out by people who have low or no formal education. Governments and donors have tendency to consider entrepreneurship as an instrument to lift up the most vulnerable population such as uneducated women, school drop outers and people with disabilities. However, there is a shortage of technological entrepreneurship in developing countries. This paper investigated the influential factors affecting the entrepreneurial motivation, intentions and decisions among African scientists and engineers’ postgraduates from China universities since 1995 to 2014. Only 6% of respondents are in technological entrepreneurship related to their field of graduation. Conclusion remark is given to encourage technological entrepreneurship which will provide more opportunities, create jobs and improve people’s quality of life.

Introduction

Technological entrepreneurship is considered an important and major key to lift and lead the regional economy towards success. In this era of competition based on technology, the regions which succeed prioritise and implement the strategies facilitating technological entrepreneurship (Carayannis & Von Zedtwitz, 2005; Yoshino & Rangan, 1995). Therefore, several governments have been establishing favourable systems for entrepreneurship such as a good infrastructure, and flexible regal and financial systems. Despite the great effort to motivate entrepreneurial activities, developing countries lack the basic advantages to strive for success in technological entrepreneurship. Although various factors such as lack of capital, unskilled workers and political instability may have contributed to the scarce of technological entrepreneurship in Africa, educated people’s positive perception on entrepreneurship is a key step to embark on entrepreneurship career. However, educated people with know-how technological skills would boost the technological entrepreneurship in developing countries. Technological entrepreneurship requires well-trained people who would face the risks with courage to persist on long-term success.

Since the end of the last decade, scholars and observers agree that Africa is undergoing a rapid pace of entrepreneurship (Ahmed, Ahmed & Nwankwo, 2013; Bruton, Filatotchev, Si & Wright, 2013). According to the 2012 Global Entrepreneurship Monitor (GEM) report, Sub-Saharan-Africa (SSA) Total Early-Stage Entrepreneurial Activity (TEA) rates were significantly higher than all other regions around the world at 28 per cent. Countries like Zambia (41 per cent), Ghana (37 per cent), Nigeria (35 per cent) and Angola (32 per cent) show some of the highest TEA levels in the world. The SSA countries have over twice as many start-ups as established businesses, in Angola (32 per cent vs. 5 per cent), Botswana (28 per cent vs. 6 per cent), Malawi (36 per cent vs. 11 per cent) and Zambia (41 per cent vs. 4 per cent) (Xavier, Kelley, Kew, Herrington & Vorderwülbecke, 2013). However, a recent study on ten countries (Angola, Botswana, Ethiopia, Ghana, Malawi, Namibia, Nigeria, South Africa, Uganda and Zambia) revealed that entrepreneurship in SSA is concentrated on retails, hotels and restaurants whereas industries based on knowledge and technology are still scarce (Herrington & Kelly,, 2012). Consequently, it seems that, to some extent, quality has been sacrificed in favour of quantity as far as entrepreneurship in SSA is concerned.

Some studies asserted that the more people go further in formal education, the higher is the motivation to pursue entrepreneurship careers (Dana, 1995; Ertuna & Gurel, 2011; Robinson & Sexton, 1994). While the latter statement seems to be true in developed countries, it constitutes the opposite fact in developing economies and particularly in Africa. For instance, all reward and benefits being equal, a big number of North African youth would prefer to work for the government than in the private or other sectors (Outlook, 2010). According to the 2012 GEM Sub-Saharan African Regional Report, only 3 per cent of entrepreneurs in Malawi, Uganda and Ghana had completed secondary levels of education (Herrington & Kelly, 2012). Van der Sluis, Van Praag and Vijverberg (2005) found that a large number of educated people in developing economies tend to prefer employment to entrepreneurship. Their study revealed that the entrepreneurial intentions tend to increase at the low levels of formal education and decrease as people achieve higher levels. Furthermore, the people with less education in developing countries will end up in necessity entrepreneurship and its impact on economic development is likely to be neutral or even negative (Acs, 2006).

Knowledge and technological based entrepreneurship is a key towards a sustainable economy and success in this pace of development. Empirical evidence suggests that an economy that fosters (a few) high impact entrepreneurial firms and high-growth firms is superior to an economy that tries to maximise the number of small and medium enterprises (SMEs) or the rate of self-employment (Shane, 2008). Technological entrepreneurship facilitates development from the individual to prosperity of a nation. For example, technological entrepreneurship has been bolstering the development of countries of emerging economy such as China, India, Brazil and South Africa, particularly in biotechnology and information science. Technological entrepreneurship is one of the tools set by the UN to achieve the millennium goals. If people are equipped with the right practical knowledge and entrepreneurship skills, sooner or later entrepreneurship will shape its road in Africa. Although entrepreneurs may hire the experts and managers, it is very important for them to have a certain level of knowledge of the industry in which they are willing to venture as well as some entrepreneurial skills in order so that they can know when they are doing right or wrong.

Traditionally, in many African countries, entrepreneurship has been somehow considered as a ‘no other option’ kind of career. Consequently, for a long time entrepreneurship in Africa has been practised by people who have low or no formal education at all. Even today to some extent, several African governments and sponsors still have a tendency to use entrepreneurship as an instrument to lift up less privileged populations, including uneducated women, youth drop-outs, people with disabilities and other social groups who live with some kind of vulnerability. Although we are not definitely insinuating that entrepreneurship is bad for these groups of people neither denying that it will positively impact their lives, we are simply suggesting that if Africa is looking forward for the sustainable development and competitive capabilities of the whole continent, there is a likelihood that this kind of entrepreneurship alone will not take it far.

Without technological entrepreneurship, it is not easy to achieve the Schumpeterian kind of entrepreneurship. The one which is believed to be the engine of development and brings innovative change into society (Anokhin, Grichnik & Hisrich, 2008; Holcombe, 1998; Schumpeter, 2013). Technological entrepreneurship has boosted the big economies in Europe and United States and has raised the formerly weak economies in Asia notably, Singapore, India, china and other countries in South Asia and Latin America, it has transformed many regions such as Silicon Valley in the United States and Bangalore in India. Admittedly, Silicon Valley may not be what Africa needs, but through knowledge and technological based entrepreneurship, it would be possible to develop its agricultural sector, food processing, sanitation and other important areas that would bring a significant change to the welfare of its citizens.

Indeed, innovative ideas originate from well-educated and knowledgeable individuals (Venkataraman, 2004). In other words, formal education has been an embryo of technological innovation and ideas. It is obvious as argued by Venkataraman (2004), that top-tier universities and research institutions play an essential role in transforming regions into hubs of technological innovation and entrepreneurship success. Few scientific researchers have addressed the factors which push formally educated people from developing countries out of entrepreneurship. Why does a high ratio of the highly educated population in developing countries not perform entrepreneurship? Do they lack entrepreneurship self-efficacy? How do they perceive entrepreneurship benefits over employment? Do they have entrepreneurship intentions at all? Up to now, there is no convincing scientific response to these questions. This article investigates the perceived value of entrepreneurship, entrepreneurship motivation and entrepreneurship decision among African science and engineering masters or PhD postgraduates trained from Chinese universities. The main objective of this study was to investigate the effect of science, engineering and technology education on the development of technological entrepreneurship in Africa. Specifically, the impact of Chinese educational training and technological exposure in stimulating entrepreneurial motivation and entrepreneurship perceived value of Africans students trained in Chinese universities.

Brief Review of Literature

Motivation to Become an Entrepreneur

Various theories have tried to explain the motives behind entrepreneurship decision. A recent comprehensive review summarised the literature of entrepreneurial motivation under five psychological and one economical perspectives (Heinrichs & Walter, 2013): (a) trait: some people have characteristics which best suit an entrepreneurship career, (b) cognitive: some people have a more positive, possibly biased evaluation of being an entrepreneur and therefore start new ventures, (c) affective: emotions and feelings exert a strong influence on the cognitive evaluation of an entrepreneur, and thereby influence the decision to create a new venture, (d) intentions: some individuals (intend to) start new ventures because they perceive this option as more desirable and more feasible than others, (e) learning: individuals observe entrepreneurial role models and tend to imitate their behaviour under certain conditions and (f) economic: individuals rationally choose self-employment based on a cost–benefit rationale. This article’s interest is primarily limited to the latter perspective.

The GEM defines entrepreneurial motivation by identifying two kinds of entrepreneurs: the ones who have been pulled into entrepreneurship by their own will for benefits such as independence, increased earnings and opportunities (the opportunity entrepreneur); as opposed to the one who have been pushed into entrepreneurship by factors other than career choice, such as lack of other alternatives, dissatisfaction with the former job (the necessity entrepreneur) (Bosma, Acs, Autio, Coduras & Levie, 2008). Whether it is out of necessity or opportunity, the entrepreneurial idea is worth pursuing only if the owner perceives certain benefit(s) from it. Segal, Borgia and Schoenfeld (2005) suggested that a person’s motivation to pursue an entrepreneurship career will primarily depend on the following key factors:

Individuals compare the desirability of self-employment with the desirability of working for others.

Individuals assess whether they possess the requisite knowledge, skills and abilities to perform the tasks and activities necessary to become an entrepreneur.

Individuals determine whether they are willing to accept the inherent risk of entrepreneurial activity.

Although, entrepreneurs are often recognised for their high risk tolerance capacity, it would be unreasonable to expect that they will blindly throw themselves into risks. Entrepreneurship decision is not an act of heroism rather it involves balancing alternatives and costs–benefits evaluation.

Balancing Employment and Entrepreneurship

There is a reason why people wake up every morning and go to work—‘work expectations’ that are goals or rewards people seek through their work. They are expressions of more general human values in the context of the work setting (Schwartz, 1999). Literature has classified work values into four categories: intrinsic (personal growth, autonomy, interest and creativity), extrinsic (pay and security), social (contact with people and contribution to society) and power (prestige, authority and influence) (Schwartz, 1999; Surkis, 1992).

Similarly, Schein (1996) suggested that, peoples’ work motivation is driven by career anchors. Career anchors are defined as what a person is never willing to give up on once faced with career choices. The eight anchors proposed by Schein include: (a) technical, (b) general managerial, (c) entrepreneurial creativity, (d) security, (e) autonomy, (f) pure challenge, (g) dedication and (h) lifestyle. Therefore, an individual’s motivation to get self-employment or work for others will depend on what extent he/she perceives the possibility of attaining his/her desired anchor(s).

According to human capital theory, people expect to be compensated by their human capital investments (Becker, 1964). As stated, anything owned costs all the trouble of getting it and it can only be traded for something more valuable for the person who owns it.

The real price of everything, what everything really costs to the man who wants to acquire it, is the toil and trouble of acquiring it. What everything is really worth to the man who has acquired it, and who wants to dispose of it or exchange it for something else, is the toil and trouble which it can save to himself, and which it can impose upon other people. (Smith, 1776)

Therefore, educated people will choose entrepreneurship over employment only if the former yields a greater reimbursement of their educational investment than does the latter.

Adapted from the existing models (Segal, Borgia & Schoenfeld, 2005; Wu & Li, 2011), we constructed our new research working model of entrepreneurial motivation. The model proposes that every work (be it employment or self-employment) has its benefits and sacrifices and a person will always balance the two in order to do or not do the work. Although, the perceived value of the work may not always equal the real value of it, under normal circumstances, perceived benefits should always exceed perceived sacrifice for the work to be worth being pursued.

Work Benefits

Work benefits could be defined as whatever reward an individual is expecting to gain from work done. They include Emotional value (emotional satisfaction gained from the work itself); Economic value (monetary and other tangible benefits gained from work); Social value (interpersonal relationship, networking, prestige and sense of belonging associated with the work); Epistemic value (new knowledge acquired and capacity building gained from work); and Self-actualization value (other intangible benefits that may make the work more desirable and meaningful to the person). For an entrepreneur, the work benefits include but are not limited to independence, creativity, leadership and feelings of achievement.

Work Sacrifices

Despite the rewarding benefits associated with any kind of work, there is always a price to pay: work sacrifices. The latter are defined as all troubles people go through in daily work in order to achieve their desired job outcomes. Contrary to the perceived benefits, employment and self-employment only share one dimension of perceived work sacrifice. Non-monetary sacrifices refer to intangible inputs people spend for their work whether employed or working for themselves. These include time, energy, effort and emotions. Moreover, entrepreneurship also involves a monetary sacrifice which covers all expenses that can be calculated including the capital, taxes, R&D, labour costs and other expenses.

A person will be motivated to entrepreneurship, if her/his perceived value of entrepreneurship is greater than the perceived value of employment (Figure 1).

Objectives of the Study:

Investigate the perceived value of entrepreneurship among African scientists and engineers as opposed to employment.

Examine the relationship between respondents’ perceived net value of entrepreneurship, entrepreneurship intentions and their decisions.

Figure 1

Source: Adapted from Segal et al. (2005) and Wu & Li (2011).

Methodology

This article used a survey questionnaire to collect data. First, the questionnaire was piloted to Rwandan postgraduates (sixteen PhD and fifty-eight masters) from Chinese universities who are currently working in Rwanda. The results were analysed and some corrections were made. The data used in this article were collected during the summer vacation of 2014 (July–August). A sample of 400 was taken from ten countries (forty participants in each country); Kenya, Tanzania, Rwanda, Burundi, Uganda, Congo Republic, Zambia, Nigeria, Ghana and Sudan. In order to reach out respondents, leaders from the above countries’ Diaspora were tracked and requested to initiate contact with the respondents willing to participate in the research. Figure 2 represents the sample description including gender, age, field of study and work experience.

In some countries such as Rwanda, Burundi, Democratic Republic of the Congo (DRC), Uganda and Tanzania, the researcher distributed the questionnaires in person and explained the instructions and the purpose of the research during reunion meetings of unions of people graduated from China. In the case of Ghana, Nigeria, Kenya, Zambia and Sudan, the researcher explained procedures to the leader or volunteer of the group who in turn informed. In total, we collected 334 questionnaires out of 400 distributed that were qualified for analysis and interpretation.

Figure 2

Source: Data of this work.

Sampling: the sample for this study was composed of 400 African science and engineering masters or PhD postgraduates from universities in China. In this investigation, we used simple random sampling technique where every individual in the sampling frame (i.e., desired population) has an equal and independent chance of being chosen for the study (Onwuegbuzie & Collins, 2007). Criteria were set beforehand the survey and limited in scope of the people post-graduated in science and engineering majors from Chinese universities. Since the time of Africa’s colonisation, African students have always considered western countries as the primary location to pursue their higher education, especially for masters and doctorate degrees. However, the situation has remarkably changed since the last decade. Asia has become the second alternative for African students to continue their educational degrees especially in science and technology majors. Since 2003, the number of African students coming to study in China has increased by 20 per cent every year, for example, the number of African students increased from 2,757 students in year 2005 to 12,436 students by 2009 (Ferdjani, 2012).

Measurement: in this study, the twenty-five items to measure the first independent variable (work perceived value) were directly taken from the study of Brenner, Pringle, and Greenhaus (1991) as they were adapted from the study of Manhardt (1972). Then, each job characteristic was categorised in one of the five dimensions in the model (Figure 1). The second independent variable (work perceived sacrifices) was constructed based on the published literature and the work of Wu and Li (2011); the reliability coefficients of independent variable sub-scales were statistically significant above Cronbach’s α: 0.7 (perceived benefits: 0.889, perceived sacrifices: 0.717). The dependent variable (entrepreneurial intention) was measured using items taken from a validated entrepreneurship intention questionnaire (EIO) (Liñán, Rodríguez-Cohard & Rueda-Cantuche, 2011).

Analysis: the empirical analysis used in this study has unique novelty in the sense that the independent variable (net perceived value of entrepreneurship) was obtained by subtracting entrepreneurship perceived value from employment perceived value. People who perceive fulfilment and contentment in organisational employment are less likely to consider entrepreneurship as an alternative career whereas those who perceive less satisfaction in employment desire to become self-employed (Brenner, Pringle & Greenhaus, 1991). Hypothetically, a positive perceived value in entrepreneurship would result in high entrepreneurial intentions whereas a negative perceived value would yield in low entrepreneurial intentions. As Wu suggested ‘perceived value of entrepreneurship is a higher order construct that comprises two components, namely, beneﬁts and sacriﬁces’ (Wu & Li, 2011). Both dependent and independent variables were measured on a 7-likert scale. Participants were asked to rank their perceived importance of each work benefit, from a list composed of twenty-five items and rank to what extent they perceived the achievability of each benefit through employment and self-employment. Likewise, participants were asked to rank a list of work sacrifices composed of six items according to how uncomfortable they would feel and which level of each sacrifice they thought could be avoided or minimised through both careers. Finally, they were asked to indicate their entrepreneurship intentions by responding to one yes–no question and, ranking six items on 7-likert scale.

First, the demographic characteristics for our sample were analysed. Afterwards, means and standard deviations were calculated to determine how much importance respondents perceived in each job value and the level of discomfort they perceived in each job sacrifice. Furthermore, we conducted paired sample t-tests to determine mean differences between perceived value of entrepreneurship and employment. Finally, we did a Pearson correlation to determine the relationship between independent variables (net perceived value of entrepreneurship) and the dependent variables (entrepreneurship intentionality).

Results

Out of 400 selected samples, we received 370 responses and 334 were qualified to be used in our analysis. Sample was described on four demographic criteria: (a) gender: 236 males and 98 females, (b) nationality: 17 from Burundi, 41 from DRC, 39 from Ghana, 33 from Kenya, 52 from Nigeria, 35 from Rwanda, 29 from Sudan, 46 from Tanzania, 19 from Uganda and 23 from Zambia, (c) major of study: 113 in Engineering, 86 in information technology, 78 in physical science and 57 in life science and (d) area of employment: 60 were employed in government, 139 were employed in private sector, 21 were technological entrepreneurs and 114 were non-technological entrepreneurs (Figure 1).

As results show (Table 1), respondents perceived much benefit in self-employment than in being employed. Notably, self-employment was perceived as source of high monetary income (M = 6.35, SD = 0.928), provider of comfortable working conditions (M = 6.31, SD = 0.905) and a sense of accomplishment (M = 6.10, SD = 0.975). Among the twenty-five items used as job benefits in this study, nineteen of them were perceived as very important to respondents and were all perceived to be achieved through self-employment rather than in employment (Table 1). The four benefits which outperformed others in terms of perceived importance were Intellectual Stimulation, ranked of first importance with M = 6.78 followed by Independence (M = 6. 72), Job Security (M = 6.71) and Working with People of his/her own Admiration (M = 6.71). The items ranked of least importance were Routine Time and Place, Working with Congenial Associates and Fixed Rules. Surprisingly, Recognition scored very low and its perceived achievement was a bit higher in employment than in entrepreneurship. The use of educational knowledge was perceived to be quite close both in entrepreneurship (4.27) and employment (4.45).

Table 1

Means, Standard Deviations of Job Benefits Importance, Their Perceived Achievement through Employment & Self-employment

Job Perceived Benefits	N	Importance		Employment		Self-employment
Job Perceived Benefits	N	Mean	SD	Mean	SD	Mean	SD
Epistemic Values
Creativity	334	6.20*	1.088	3.49	1.501	6.43**	.862
Use of Educational KN	334	5.95	1.119	4.27	1.327	4.45	1.625
Variation in Work	334	6.26*	.755	3.07	1.005	5.99**	.905
Intellectual Stimulation	334	6.78*	.413	5.11	1.128	6.21**	.910
KN Development	334	6.36*	.896	4.90	1.213	6.02**	.913
Economic Values
Money	334	6.62*	.598	2.60	.757	6.35**	.928
Job Security	334	6.71*	.573	5.05	1.270	5.74**	1.188
Fixed Rules	334	4.23	1.130	6.02	1.443	2.93	1.284
Routine Time & Place	334	2.39	.875	6.37	.922	1.90	.759
Own Way of Doing Work	334	6.72*	.469	3.39	1.309	6.50**	.856
Independence	334	6.72*	.515	2.19	.938	6.41**	.911
Emotional Values
Leisure Time	334	5.13*	1.206	4.77	1.320	4.34	1.398
Recognition	334	4.85	1.335	4.99**	1.303	3.36	1.204
Cultural Aesthetics	334	5.34*	.822	3.04	.945	5.99**	.918
Comfortable Working Conditions	334	6.59*	.565	3.33	1.046	6.31**	.905
Social Values
Congenial Associates	334	2.67	1.418	4.16**	1.424	2.51	1.375
Meeting many People	334	6.13*	.908	3.17	1.205	6.25**	.921
Respected Job	334	6.21*	.868	4.06	1.381	5.84**	.883
Social Contribution	334	6.41*	.651	4.72	1.433	5.69**	.860
Working with People of Own Admiration	334	6.71*	.456	4.13	1.271	6.00**	.950
Self-actualisation
Risk Responsibility	334	6.54*	.570	2.68	.872	6.21**	.974
Accomplishment Feeling	334	6.69*	.463	3.81	1.246	6.10**	.975
Supervising Others	334	6.51*	.691	2.46	.872	6.51**	.802
Key Role in Organisation	334	6.65*	.524	2.36	.698	6.64**	.760
Administrative Responsibility	334	6.69*	.554	3.94	1.465	6.51**	.820
Valid N (list-wise)	334

Source: Original of this work.

Notes:*perceived importance.

**perceived achievement.

KN—knowledge.

Except for Job Risks, all the remaining five job sacrifices represented a high discomfort for the respondents. Working Hours and Socialisation were perceived to be minimised through employment, whereas Health Risks and Family Related Problems were perceived to be minimised through self-employment (Table 2). We ran three paired sample t-tests for mean differences between entrepreneurship and employment. The first t-test compared perceived benefits of entrepreneurship versus employment. A two tailed paired sample t-test revealed that respondents perceived higher benefits in entrepreneurship (M = 5.4875, SD = 0.36116) compared to employment (M = 3.9221, SD = 0. 55872), t (133) = 21.776, P ≤ 0.001. The second t-test compared perceived sacrifices of both entrepreneurship and employment, the results showed that respondents perceived higher job sacrifices in self-employment (M = 3.0759, SD = 0.32548) than in employment (M = 4.9067, SD = 0.30895), t (133) = 45.388, P ≤ 0.001.

The last t-test compared the difference between total perceived values of entrepreneurship and employment. The results showed that respondents perceived higher value in entrepreneurship (M = 2.4116, SD = 0.52479) than in employment (M = −0.9846, SD = 0.62769) t (133) = −38.392, p ≤ 0.001.

Table 2

Means, Standard Deviations for Perceived Discomfort in Job Sacrifices and Perceived Minimisation through Employment & Self-employment

On Job Sacrifices	N	Degree of Discomfort		Employment		Self-employment
On Job Sacrifices	N	Mean	SD	Mean	SD	Mean	SD
Working Hours	334	6.5821	.68604	6.4030*	0.72671	1.5149**	0.72273
Job Risks	334	4.5821	2.62521	6.5149	0.65735	1.2537	0.53010
Emotional Feelings	334	5.9104	1.64734	6.3657*	0.75135	1.2463**	0.46593
Family	334	6.7910	0.40809	1.4254**	0.65324	6.3433*	1.29257
Socialisation	334	6.5224	1.19344	6.7463*	0.81052	1.4403**	0.89704
Health Risks	334	6.9552	0.20759	1.9851**	0.91754	6.6567*	0.58944
Valid N (list-wise)	334

Source: Original of this work.

Notes:* Chances to minimise sacrifice is high.

** Chances to minimise sacrifice is low.

Table 3

Model Results of Pearson Correlation Coefficient

	Entrepreneurship Intention	Perceived Net Value of Entrepreneurship
Entrepreneurship Intention	Pearson Correlation	1	0.244**
	Sig. (2-tailed)		0.005
	N	334	334
Perceived Value of Entrepreneurship	Pearson Correlation	0.244**	1
	Sig. (2-tailed)	0.005
	N	334	334

Source: Original of this work.

Note: ** Correlation is significant at the 0.01 level (2-tailed).

When they were asked whether they have ever seriously considered becoming entrepreneurs, 241 (72 per cent) respondents answered ‘Yes’, only 86 (25.7 per cent) answered ‘No’ and 2.2 per cent were not sure. Also on a 7-likert scale, they were asked to agree or disagree on statements stating their entrepreneurial intentions. 44 per cent of respondents were totally convinced to become entrepreneurs, 38.8 per cent agreed, 16.4 per cent moderately agreed, whereas 0.7 per cent were not sure.

Finally, we did a Pearson correlation between dependent and independent variables (Table 3). Net entrepreneurship perceived value was positively correlated with entrepreneurship intentionality with a significant (0.01) Pearson correlation coefficient 0.244.

About their entrepreneurship perceived value (M = 5.4875, SD = 0.36116) and entrepreneurial intention (M = 3.8197, SD = 1.43504). A Pearson’s r data analysis revealed a positive correlation, r = 0.224. Respondents who perceived high value in entrepreneurship had high entrepreneurial intentions.

Discussion

The primary starting point in this study was an attempt to find reasons behind the scarcity of entrepreneurship-based knowledge and technology in developing countries by using Africa as a case study. Following an economic approach, we introduced perceived value as a major construct that will determine an individual’s choice between employment and self-employment. Empirical results revealed that lower perceived value in entrepreneurship is far from being the cause of the shortage of entrepreneurship-based knowledge and technology.

In comparison to employment, respondents perceived many benefits in self-employment except for the area of routine time and place, working with congenial associates and fixed rules. All the other job benefits were of great importance and highly perceived through self-employment. Although respondents perceived much sacrifice in entrepreneurship as well, when both benefits and sacrifices were combined, the perceived value of entrepreneurship still outperformed the perceived value of employment with (M = 2.4116, SD = 0.52479) against (M = −0.9846, SD = 0.62769) t (133) = −38.392, P ≤ 0.001. The relationship between entrepreneurship net perceived value and entrepreneurship intentionality was statistically justified. Hence, both our research objectives were attained.

Despite the higher intentions found in respondents, the kind of entrepreneurship in which they would like to orient themselves was not studied in this article. Since entrepreneurship carried out by a highly educated person is not only classified as technological, a longitudinal study is needed to find out whether these intentions of science and engineering postgraduates will lead them to becoming technology entrepreneurs. ‘What distinguishes technology entrepreneurship from other entrepreneurship types is the collaborative experimentation and production of new products, assets, and their attributes, which are intricately related to advances in scientific and technological knowledge and the firm’s asset ownership rights’ (Bailetti, 2012).

Indeed, people are embedded in their environmental context (Ajzen, 1991; Kibler, 2013). If higher-educated people find themselves in regions where employment is more highly valued than self-employment, their entrepreneurial intentions are likely to diminish. Nevertheless, there are two main reasons why people with higher education may still choose employment even if they are highly attracted to self-employment. First, obviously entrepreneurship activity is much costlier for higher educated people as opposed to their uneducated counterparts. For educated people, capital investment in entrepreneurship includes their educational investment, the latter being equal to direct educational cost plus indirect educational cost as well as opportunity cost. Second, because entrepreneurship tends to provide return on education investment in the long term, higher educated people may have a tendency to choose employment in order to get the short-term return on their education investment. In contrast with developed countries, the pursuit of higher education in developing countries requires family and relatives to invest on limited numbers of family members. However, the desire to satisfy and pay back the family made investments may be a reason pushing several students to choose employment. We have an ongoing investigation about this factor which we believe can guide the government and investors to allocate their investments.

This article evaluated the factors influencing the entrepreneurship decisions among the respondents. It was revealed that study location, mentors or research supervisors and life style influenced some respondents to become entrepreneurs. The people who studied in China’s big cities such as Beijing, Shanghai and Guangzhou became entrepreneurs more than those who studied in small cities. The quantitative analysis shows that 28 per cent of entrepreneurs studied in Beijing, 21 per cent in Shanghai and 13 per cent in Guangzhou. When asked how they decided to become entrepreneurs, 16 per cent indicated that they just found themselves in entrepreneurship. This kind of entrepreneurship is defined in this article as accidental entrepreneurship. The majority of accidental entrepreneurs are those who are engaged in trading businesses. This seemed obvious since the emerging economy of China as hub of manufacturing led these postgraduates, aware of all the cheap products made in China, to start trading businesses between China and their home countries. The graduates from China are not only mastering the Chinese language but also understand Chinese negotiations and culture as stated by a master postgraduate in biotechnology from Xiamen University (a male from Ghana):

By the end of their educational training, most African students must have mastered the Chinese language and this provides them with an added advantage in the economically competitive world, where the addition of a foreign language puts a job seeker way above his colleagues. The cultural diversity in China gives African students in China a blend of cultural development and socialization. This is important to the future career development. Giving the fact that business activities are relatively booming in many Chinese cities than in African, many of these students begin to learn the entrepreneurial lifestyle of the Chinese and are most likely to apply that in their various countries after graduation. I strongly believe that this would culminate in an enhanced business environment and holds the future to entrepreneurship in Africa.

Most of the African graduates from Chinese universities would sometimes play the intermediate role and facilitate communication between Chinese companies/ businessmen and the buyers from their home countries. This would lead them to mastering the Chinese market which could be a useful asset in future. Doing business with Chinese businessmen would be more easier for them as stated by a PhD postgraduate (male from Tanzania) in Computer Science at University of Science and Technology of China: ‘Studing in china can help African students to start their own business, because it is very easy for them to do business with Chinese. They have the advantages of knowing chinese language and knowing chinese product.’

When asked about the importance of studying in Chinese universities towards entrepreneurship, he claimed that the opportunity identification in products and services between China and Africa is an asset to start a new business.

Entrepreneurship is arguably one of the most important inputs in the economic development of African countries, so the the education acquired in Chinese university can first help African students to enovate new product and service, which can accelerate the economic growth of African countries. That is to say the education will help African students in opportunity identification especially between China and Africa in product and service.

The observation and learning from experience equip the graduates from Chinese universities with useful knowledge in modern technology to innovate businesses and replicate some technologies as elicited from the interviews when asked the advantages of studying in China. For example, a master graduate in industrial engineering from University of Science and Technology of Beijing (USTB) (gender: female, country: Sudan, position: consultant) said:

Studying in China exposes African students to new technologies as these universities in China are far advanced in technology research. African students have the opportunity to learn the success strategies used by Chinese in their businesses both in China and abroad. It would be easier to replicate the knowledge acquired in China back home in starting our own businesses. Studying in China also can serve as a guarantee to starting your own business in Africa with the help of a bigger Chinese company.

Additionally, the networks established during their studies were advantageous for those who studied in big cities because one is more likely to meet business people in big cities rather than in small cities. A PhD postgraduate in Civil Engineering from South China University of Technology (gender: male, country: Rwanda, current position: Manager and Co-founder Wanda Money Transfer. Co.LTD) straight-forwardly revealed the importance of studying in China’s booming economy towards self-employment:

The experience to study in a Chinese university offers great opportunities to build useful connections which can be great assets to successful start a new business in Africa. Today’s worldwide business is dominated with China so that a partnership with Chinese company can help to promote a new business in Africa because the supplier chain would be rich and strong. China has a plenty of factories where a student can learn from and replicate those techniques in Africa without worrying to the copyrights.

Surprisingly, 33 per cent responded that their entrepreneurship decisions stemmed from their study mentor or supervisors. This work did not investigate whether Chinese professors or university staffs engage in business foreign graduates from their universities. Further research could explore this possibility.

Complex financial systems and political instability are significantly identified to influence highly educated people towards employment. Most developing countries have poor and corrupt financial systems due to the lack of strong institutions and thus incompetent governments. Poor financial systems constrain starters to find adequate capital to enter the competitive markets or start new ideas. Previous studies have argued that financial constraint is a key determining who becomes an entrepreneur (Holtz-Eakin, Joulfaian & Rosen, 1994; Paulson & Townsend, 2004). In contrast, people with higher education foresee and realise the risks related to the above-mentioned poor financial systems while uneducated people have no other option, except gambling in a high-risk environment. Additionally, while the people with higher education have spent most of their time in schools, the uneducated people invest their time accumulating wealth and raising sufficient capital for future businesses. Lastly, in developing countries, the allocation of capital investments into entrepreneurship is scarce and lacks the adequate follow-up to talented entrepreneurs.

Political instability has influenced several talented people to divert from entrepreneurship to employment for the safety of their resources and families. Entrepreneurial activities require a first step of sacrifice and risk before achieving success. This transition is hard to take in an unstable environment. Previous investigations have discussed that the lack of stable environments has hindered socio-economic growth (Mbaku, 1988). Political instability creates poor institutions which fail to implement the favourable policies for entrepreneurs and entrepreneurial endeavours (Dutta, Sobel & Roy, 2013). Moreover, political instability impacts the financial, judicial and regal systems.

The fact that recognition scored low on perceived importance of respondents has some cultural explanation which deserves further investigation. Sub-Saharan African countries are classified into harmony versus mastery societies. Whereas in mastery societies, people are ambitious, daring, competent and success driven and in harmony societies, people are concerned with fitting into the environment by unifying themselves with nature and accepting the world as it is (Lewis, 2006, p. 563; Schwartz, 1999) and uncertainty is highly avoided (Hofstede, 2010). To promote an entrepreneurial spirit in harmony societies, education curricula and resources are not enough. There is also a need for the adoption and development of an entrepreneurial culture.

Limitations

This study was intended to investigate entrepreneurship motivation and entrepreneurial intentions of African scientists and engineers who are postgraduates from Chinese universities. It has also limited itself to masters and PhD holders since the researchers believe that students below the said two levels are still at the starting level of their career majors and they have not yet acquired enough skills to determine their professional orientation in those fields. Despite minor difficulties encountered during the data collection, the respondents were excited to contribute to this investigation. We recommend further research accessing large samples from both postgraduates from developing countries and those from developed countries to compare their perceptions. It should be noted that this study involved psychological constructs which cannot be measured fully using a predictable measurement. Last but not least, items used to measure perceived on the job sacrifices were the authors’ self-constructions based on literature; a more standardised measurement is highly needed.

Conclusions and Implications

Theoretically, this article contributed to existing models of entrepreneurial motivation by introducing a new methodology. It compared both entrepreneurship perceived benefits and sacrifices versus employment perceived benefits and sacrifices. Specifically, it promoted the construct of net desirability for self-employment. This article tackled a neglected potential area of research ‘science and engineering’ as far as African entrepreneurship is concerned. Hopefully, this initiative will arouse more research interest in technological entrepreneurship in developing countries. The results revealed that respondents perceived higher value in entrepreneurship as compared to employment and the latter was positively correlated with their entrepreneurial intentionality. However, given the motive which pushed us to carry out this study, there is inconsistency between our results and the actual situation of entrepreneurship based knowledge and technology in Africa. While the results found positive perception and high entrepreneurship intentions among science and engineering graduates, the number of higher educated people entering entrepreneurship in Africa is still low. Human capital is a key factor grounding quality of entrepreneurship. The latter is associated with high-technology based businesses initiated by high educated individuals (Acs, Szerb & Autio, 2015). Unfortunately, African entrepreneurship continues to experience a shortage of well-trained human capital whereby some countries including Ghana, Uganda, Tanzania and Rwanda are still at low level of entrepreneurial abilities with 0.04 out of 1 as reported in GEM (Acs, Szerb & Autio, 2015). Practically, the implication is that intentions alone may not determine the action an individual will take, and that the speed of science and technology education in Africa, may not necessarily equal the speed of technological entrepreneurship. Therefore, future research could explore the possible factors moderating the entrepreneurship intentionality and the actual behaviour of entrepreneurs among the African higher-educated population.

The entrepreneurs whose prime motivation was wealth maximisation, were more likely to make a remarkable contribution in creating jobs and increasing exports (Hessels, Van Gelderen & Thurik, 2008). Hence, governments and policymakers should keep in mind that as people go further in education, they get more opportunities and alternatives through which they fulfil their basic needs such as food and shelter. And once a need has been satisfied, it is no longer a motivating factor (Maslow, 1943). Thus, higher-educated people’s motivation to become entrepreneurs is less likely to depend on basic needs as opposed to their less educated counterparts. Rather, their motivation is more likely to depend on wealth maximisation and other factors like social status, independence, security, as well as some emotional factors. It is hence recommended if the quality of entrepreneurship in Africa has to be improved, the concerned stakeholders, especially policymakers and educators, have a huge task to develop more efficient strategies which could generate more entrepreneurial activities based on knowledge and technology. Technological entrepreneurship could be promoted by creating a trustworthy conducive entrepreneurial working environment whereby innovation is encouraged, recognised and possibly rewarded. Besides, technological entrepreneurship is not a one-person thing; it requires full collaboration among institutions, fairness in regulations and effective leadership.

Footnotes

Acknowledgements

The authors thank the Chinese Academy of Science and The World Academy of Science (CAS-TWAS) for financial support and PhD fellowship. We thank Mrs Alison Sherk for editing and revising English in this manuscript.

References

Acs

(2006). How is entrepreneurship good for economic growth? Innovations, 1, 97–107.

Acs

Z. J.

, Szerb

, & Autio

(2015). The global entrepreneurship and development index. Washington, DC: Springer.

Ahmed

, Ahmed

, & Nwankwo

(2013). Entrepreneurship development in Africa: An overview. World Journal of Entrepreneurship, Management and Sustainable Development, 9(2/3), 82–86.

Ajzen

(1991). The theory of planned behavior. Organizational Behavior and Human Decision Processes, 50(2), 179–211.

Anokhin

, Grichnik

, & Hisrich

R. D.

(2008). The journey from novice to serial entrepreneurship in China and Germany: Are the drivers the same. Managing Global Transitions, 6(2), 117–142.

Bailetti

(2012). Technology entrepreneurship: Overview, definition, and distinctive aspects. Technology Innovation Management Review, 2(2), 5–12.

Becker

G. S.

(1964). Human capital theory. New York: Columbia University Press.

Bosma

, Acs

Z. J.

, Autio

, Coduras

, & Levie

(2008). Global entrepreneurship monitor. Executive report. Retrieved 23 October 2010 , from http://www.gemconsortium.org/download/1287850267108/GEM_Global_08.Pdf

Brenner

O. C.

, Pringle

C. D.

, & Greenhaus

J. H.

(1991). Perceived fulfillment of organizational employment versus entrepreneurship: Work values and career intentions of business college graduates. Journal of Small Business Management, 29(3), 62.

10.

Bruton

G. D.

, Filatotchev

, Si

, & Wright

(2013). Entrepreneurship and strategy in emerging economies. Strategic Entrepreneurship Journal, 7(3), 169–180.

11.

Carayannis

E. G.

, & Von Zedtwitz

(2005). Architecting gloCal (global–local), real-virtual incubator networks (G-RVINs) as catalysts and accelerators of entrepreneurship in transitioning and developing economies: Lessons learned and best practices from current development and business incubation practices. Technovation, 25(2), 95–110.

12.

Dana

L.P.

(1995). Entrepreneurship in a remote sub-Arctic community. Entrepreneurship Theory and Practice, 20(1), 57–72.

13.

Dutta

, Sobel

R. S.

, & Roy

(2013). Entrepreneurship and political risk. Journal of Entrepreneurship and Public Policy, 2(2), 130–143.

14.

Ertuna

Z. I.

, & Gurel

(2011). The moderating role of higher education on entrepreneurship. Education+ Training, 53(5), 387–402.

15.

Ferdjani

(2012). African students in China: An exploration of increasing numbers and their motivations in Beijing. Stellenbosch South Africa: Centre for Chinese Studies.

16.

Heinrichs

, & Walter

(2013). Who becomes an entrepreneur? A 30-years-review of individual-level research and an agenda for future research. Journal of Small Business and Enterprise Development, 22(2), 225–248.

17.

Herrington

, & Kelly

(2012). African entrepreneurship: Sub-Saharan African regional report. Global Entrepreneurship Monitor. The graduate school of Business/University of Cape Town.

18.

Hessels

, Van Gelderen

, & Thurik

(2008). Entrepreneurial aspirations, motivations, and their drivers. Small Business Economics, 31(3), 323–339.

19.

Hofstede

(2010). Dimensionalizing cultures: The hofstede model in context. Retrieved from http://scholarworks.gvsu.edu/cgi/viewcontent.cgi?article=1014&context=orpc

20.

Holcombe

R. G.

(1998). Entrepreneurship and economic growth. Quarterly Journal of Austrian Economics, 1(2), 45–62.

21.

Holtz-Eakin

, Joulfaian

, & Rosen

H. S.

(1994). Sticking it out: Entrepreneurial survival and liquidity constraints. Journal of Political Economy, 102(1), 53–75.

22.

Kibler

(2013). Formation of entrepreneurial intentions in a regional context. Entrepreneurship & Regional Development, 25(3/4), 293–323.

23.

Lewis

R. D.

(2006). When cultures collide: Leading across cultures. Boston, London: Nicholas Brealey Publishing.

24.

Liñán

, Rodríguez-Cohard

J. C.

, & Rueda-Cantuche

J. M.

(2011). Factors affecting entrepreneurial intention levels: A role for education. International Entrepreneurship and Management Journal, 7(2), 195–218.

25.

Manhardt

P. J.

(1972). Job orientation of male and female college graduates in business. Personnel Psychology, 25(2), 361–368.

26.

Maslow

A. H.

(1943). A theory of human motivation. Psychological Review, 50(4), 370.

27.

Mbaku

(1988). Political instability and economic development in Sub-Saharan Africa: Some recent evidence. The Review of Black Political Economy, 17(1), 89–111.

28.

Onwuegbuzie

A. J.

, & Collins

K. M.

(2007). A typology of mixed methods sampling designs in social science research. The Qualitative Report, 12(2), 281–316.

29.

Outlook

R. E.

(2010). Sub-Saharan Africa. Washington, D.C: International Monetary Fund.

30.

Paulson

A. L.

, & Townsend

(2004). Entrepreneurship and financial constraints in Thailand. Journal of Corporate Finance, 10(2), 229–262.

31.

Robinson

P. B.

, & Sexton

E. A.

(1994). The effect of education and experience on self-employment success. Journal of Business Venturing, 9(2), 141–156.

32.

Schein

E. H.

(1996). Career anchors revisited: Implications for career development in the 21st century. The Academy of Management Executive, 10(4), 80–88.

33.

Schumpeter

J. A.

(2013). Capitalism, socialism and democracy. London: Routledge.

34.

Schwartz

S. H.

(1999). A theory of cultural values and some implications for work. Applied Psychology, 48(1), 23–47.

35.

Segal

, Borgia

, & Schoenfeld

(2005). The motivation to become an entrepreneur. International Journal of Entrepreneurial Behaviour & Research, 11(1), 42–57.

36.

Shane

(2008). The Illusions of Entrepreneurship. New Haven, CT: Yale University Press.

37.

Smith

(1776). The wealth of nations, Book 1. London: Methuen & Co.

38.

Surkis

(1992). Work values: Influences of basic individual values and education level on their importance (Unpublished master’s thesis). The Hebrew University, Jerusalem.

39.

Van der Sluis

, Van Praag

, & Vijverberg

(2005). Entrepreneurship selection and performance: A meta-analysis of the impact of education in developing economies. The World Bank Economic Review, 19(2), 225–261.

40.

Venkataraman

(2004). Regional transformation through technological entrepreneurship. Journal of Business Venturing, 19(1), 153–167.

41.

, & Li

(2011). Perceived value of entrepreneurship: A study of the cognitive process of entrepreneurial career decision. Journal of Chinese Entrepreneurship, 3(2), 134–146.

42.

Xavier

, Kelley

, Kew

, Herrington

, & Vorderwülbecke

(2013). Global entrepreneurship monitor (GEM) 2012 global report. Kuala Lumpur: GERA.

43.

Yoshino

M. Y.

, & Rangan

U. S.

(1995). Strategic alliances: An entrepreneurial approach to globalization. Boston: Harvard Business Press.