Prof. Pradeep S. Chauhan, Centre for Economic Studies & Planning (CESP), School of Social Science (SSS-II), Jawaharlal Nehru University (JNU), India
Vaibhav Verma, Research Scholar, Department of Economics,, Kurukshetra University Kurukshetra
Abstract
Over the years, there is a significant growth in new technologies and new business models. New jobs will demand new types of skills to compete in the labor market. Skill development will resolve two essential things in India: one is unemployment, and another is poverty. The research is crucial to understanding how graduates in India see entrepreneurial abilities. Having realized the alarming situation of our future of youth and the Indian economy, the researcher focused on understanding the entrepreneurial skill attitude of graduates, particularly in Kurukshetra and Kaithal. The author created a comprehensive entrepreneurship skill attitude questionnaire with five points scale. The survey was collected as primary data and distributed through a Google Form. The objectives are to determine the differences, associations, and relationships between selected independent variables. The survey questionnaire tool was standardized with a committee of experts and validated with a pretest. A random sampling of 350 students was taken from the districts of Kurukshetra and Kaithal.
Keywords: Entrepreneurship, Employability, Skill Development.
Introduction:
Every graduate hopes to land a well-paying career. All the educational institutes aim to enhance graduates’ skills through various upskilling programs. India boasts the world’s youngest population. In the next 20 years, it is anticipated that its work force would rise by 32%. Giving our youthful labour force the necessary information, marketable skills, and greater entrepreneurship is one of India’s biggest difficulties. Over the years, there is a significant growth in new technologies and new business models. Covid 19 has overhauled many jobs and paved the way for new jobs. New jobs will demand new types of skills to compete in the labor market. Skill development will resolve two essential things in India: one is unemployment, and another is poverty. Economic liberalisation has increased job prospects significantly, particularly in the industrial and service sectors (Agrawal, 2014; Mehrotra & Ghosh, 2014). The employment element in the manufacturing sector was negatively impacted by economic expansion, which did not materialise in employment (Dev, 2013). In this jobless scenario, India has faced several challenges in making skilled laborers (Agrawal, 2012).
Significance of the Research Problem
* Decreasing Employment Ratio
* The increasing gap between graduates/ postgraduates and employment
* The scenario of the recent pandemic’s impact
The research is crucial to understanding how graduates in India see entrepreneurial abilities. The following was estimated in the most recent Future of Jobs study by the World Economic Forum (Schwab & Zahidi, 2020). A shift in how people and robots share resources might result in the displacement of 85 million jobs by 2025, yet more than 97 million brand-new occupations that are unimaginable to us now could also be created. The new labour force avatar is more suited for these new tasks (Schwab & Zahidi, 2020). When compared to 92 percent in the USA, 52 percent in the UK, and 45 percent in Japan, just 7 percent of the labour force in India has a higher education (Swaminathan, 2008). However, if the nation fails to develop entrepreneurial skills and upskill the labor force, the manufacturing industries will face the catastrophe of a shortage of skilled people, which would face a terrific mismanagement of labor (Batra, 2009; King, 2012; Mishra, 2014). This situation initiated the researcher to identify the perception of young India toward entrepreneurship skills. However, the emerging new jobs and skills will create a quantum of the skills gap, and skill mismatch will continue to halt the economy of the developing countries(Allen & de Grip, 2007; Bergin et al., 2019; Musa & Al-Rubaie, 2021). The McKinsey report (Ellingrud et al., 2020) points out that upskilling challenges will be more for various sectors such as manufacturing, transportation, retail, etc. Having realized the alarming situation of our future of youth and the Indian economy, the researcher focused on understanding the entrepreneurial skill attitude of graduates, particularly in Kurukshetra and Kaithal.
Review of Literature
Importance of Skill Development
The COVID-19 pandemic has significantly affected every human capital sector, paving the way to new horizons (International Labour Organization (ILO, 2021). A trained and educated labour is one of the primary foundations of a knowledge economy, according to a World Bank Institute research on India and the Knowledge Economy (Batra, 2009). It is extremely important to remember that one of the Millennium Development Goals is to guarantee that people have an improved quality of life (Dev, 2013). According to the Ransstad research, skilling, upskilling, and reskilling will be key variables in determining future employment (Randstad, 2020). The country should work to improve the working force’s skills and employment status through innovation (Pattanaik & Nayak, 2013). This shocking scenario necessitated the Indian government to form new policies and schemes to make a skillful labor force in the 21st century and through the qualification-skill framework, emerged the National Skill Development Policy in 2009 (Blumenfeld & Malik, 2017).
The ecosystem of Learning Organization
According to a Boston Consulting Group report, India will have an excess of labour (47 million people) by 2020, while the rest of the globe would experience a 56 million manpower shortfall (BCG, 2007). A shifting labour market dynamics and unpredictable futures are represented by upskilling, reskilling, and skilling (Suri, 2021). Additionally, Randstad Risesmart global survey discovered that about 70% of 1000 HR employees need to retrain or upskill in order to adapt to a changing workplace (Randstad, 2020). Similarly, 2020 Deloitte’s report affirms that 74% of the workforce requires reskilling their workforce for the next 12 to 18 months (Deloitte, 2020). International organizations such as Walmart and Google have heavily invested in upskilling resources in the foreseeable future (Gichobi, 2022).
Institutional and Regulatory Measures of Skill Development in India
The eleventh five-year skill development plan can help to implement the core idea of the higher education plan (Agrawal, 2012). The Prime Minister’s National Council on Skill Development (PMNCSD) and the National Skill Development Coordination Board (NSDCB) were the two organisations created as a result of this initiative (Dev, 2013). In order to act as a link between the centre and industry, the National Skill Development Corporation (NSDC) was conceived in 2008. Additionally, the government gave money to those in need (Das, 2015). By 2022, the organisation intended to have 500 million skilled workers (Agrawal, 2012). The Skill Sector Centre (SSC), which has 1661 Qualification Packs and covers 4420 standards, will carry out the projects (Tara & Kumar, 2016). The “Skill Development Mission” is the focus of the five-year plan, which calls for a significant investment of Rs 228 billion (Agrawal, 2012). The emphasis of the 12th Five-Year Plan was on job creation and skill development (Dev, 2013). To foster a trained workforce in the Indian economy, the National Skill Development Agency (NSDA) was established (Das, 2015). To better oversee activities, the Indian government established the Ministry of Skill Development and Entrepreneurship (Tara & Kumar, 2016). A number of institutional improvements have been started by the Ministry to provide efficient training programmes (Ahmed, 2016). By 2022, the programme is expected to produce a skilled work force of 402.9 million people (Ahmed, 2016). Besides, as part of the Skill India Mission, Pradhan Mantri Kaushal Vikas Yojana (PMKVY) was launched in 2015 (Tara and Kumar, 2016). In 2014, the center established national skill universities and passed a bill. Then from 2018 onward, Maharashtra, Odisha, Haryana, Kerala, Rajasthan, Madhya Pradesh, and Gujarat have started skill universities in the states (Abhay, 2023).
Entrepreneurial Models in Higher Education Institutions
It is thought that education might help spread entrepreneurship (Fietze & Boyd, 2017; Saeed et al., 2015). Entrepreneurial education and students’ intents are positively correlated, according to human capital theory, entrepreneurial self-efficacy, and self-determination theory. It equips students with the necessary information and abilities and inspires them to pursue careers as entrepreneurs (Boldureanu, 2020). Self-efficacy is the driving force to enhance entrepreneurial intention. Education and intention are essential in undertaking new ventures (Asimakopoulos et al., 2019). Edmilson et al., 2015 propose opportunities to improve entrepreneurship education. Higher education lays a foundation to develop entrepreneurial potential among young people (Varamaki et., 2015). Entrepreneurship education will become more effective when the graduates are allowed to have industrial skill training with full intention rather than classroom teaching (Hassan et al., 2020).
Figure 1: Theoretical Framework
Entrepreneurship education
Attitude, Motivation, Skills, Knowledge
Existing educational institutions
Positive
Negative
Skilled entrepreneurs with better knowledge and attitude
Undergo Skill Training and intervention
Objectives & Methodology
The research study investigates the perception of Indian graduates regarding employability skills in the current post-COVID pandemic and challenging economic scenario. Since the researcher’s main objective was to observe, quantify, and characterise the entrepreneurial skill attitude among college students in Kurukshetra and Kaithal, a descriptive research design was used for this study. The author created a comprehensive entrepreneurship skill attitude questionnaire with five points scale. The survey was collected as primary data and distributed through a Google Form. The objectives are to determine the differences, associations, and relationships between selected independent variables. The survey questionnaire tool was standardized with a committee of experts and validated with a pretest. A random sampling of 350 students was taken from all the districts of Kurukshetra and Kaithal. This analysis used the statistical package of SPSS version 25 to compute the data.
Analysis, Findings & Discussions
Independent Variables (350 Samples)
Table 1. Measurement of independent variables
Independent Variables
Categories
Total
%
Age
19 to 22
239
72
23 & to 25
54
16
26 & Above
39
12
Gender
Male
117
33
Female
233
64
Residence
Urban
209
60
Rural
141
40
Family Type
Nuclear
231
66
Joint
67
19
Separated
52
15
Generation
First
187
53
Second
163
47
Community
DSC
3
1
GEN
190
54
BC-B
98
28
BC-A
20
6
SC
39
11
Education
UG
245
70
PG
96
28
Ph.D.
8
2
College type
Adied
150
43
Government
186
53
Private
14
4
College location
Urban
190
54
Rural
160
46
Subject
Science
170
49
Arts
161
46
Technical
19
5
Source: Primary Data
Independent variables are taken to measure the attitude levels in any scientific research work. The following independent variables were treated with 350 samples taken from throughout Kurukshetra and Kaithal. Observations are narrated below for all variables such Age groups: 72% of 10 to 22, 16% of 23 to 25, and 12% of 26 & above age groups. Gender groups: 33% of Male and 64% of female students. Residences: 60% of Urban and 40% of rural students. Family types: 66% of Nuclear, 19% of joint, and 15% of Separated families. Generation of study: 53% of first and 47% of the second generation students. Communities: 1% of DSC (Deprived Scheduled Caste), 54% of GEN, 28% of BC-B, 6% of BC-A, and 11% of SC. Educational Qualification: 70% of UG, 28% of PG, and 2% of Ph.D. students. College types: 43% of Adied , 53% of Government, and 4% of private run colleges. Location of the Colleges: 54% of Urban and 46% of rural colleges and Subjects studying: 49% of Science, 46% of Arts, and 19% of Technical education.
Figure 2. Total Entrepreneurship Attitude
The general entrepreneurship attitude among College students of Kurukshetra and Kaithal out of 350 samples collected was 50% of Average, 25% High, and another 25% low. This attitude confirms the trends reflected in the research conducted in different countries, especially among the developing ones.
Figure 3. Entrepreneurship Attitude (Categories)
Students generally have an average level of motivation, i.e., 54% in entrepreneurship activities. This average level is mostly reflected in all other categories of knowledge (49%), Influences (50%), and huddles (51%) faced by the students’ communities throughout Kurukshetra and Kaithal. The increase in motivation, along with other areas, should be promoted to achieve the goals of entrepreneurship development.
ANOVA (Test Of Difference)
Table 2. Table showing the Anova Test
Sum of Squares
df
Mean Square
F
Sig.
Gender
Between Groups
.836
2
.418
1.882
.154
Within Groups
77.053
347
.222
Total
77.889
349
Age
Between Groups
.235
2
.118
.246
.782
Within Groups
157.283
329
.478
Total
157.518
331
Community
Between Groups
.483
2
.241
.239
.787
Within Groups
350.077
347
1.009
Total
350.560
349
Education
Between Groups
.557
2
.278
.763
.467
Within Groups
126.183
346
.365
Total
126.739
348
Subjects
Between Groups
4.239
2
2.120
6.149
.002**
Within Groups
119.615
347
.345
Total
123.854
349
College type
Between Groups
.105
2
.052
.164
.849
Within Groups
111.050
347
.320
Total
111.154
349
College location
Between Groups
1.668
2
.834
3.398
.035*
Within Groups
85.189
347
.246
Total
86.857
349
Residences
Between Groups
.906
2
.453
1.887
.153
Within Groups
83.291
347
.240
Total
84.197
349
Family Type
Between Groups
10.128
2
5.064
9.691
.000**
Within Groups
181.326
347
.523
Total
191.454
349
Annual Income
Between Groups
6.093
2
3.047
7.458
.001**
Within Groups
141.761
347
.409
Total
147.854
349
Generation
Between Groups
1.138
2
.569
2.297
.102
Within Groups
85.951
347
.248
Total
87.089
349
Source: Primary Survey
ANOVA test reveals the following inferences. Among the gender groups, the P value (.154) is more than 0.050, and there is no significant difference found among the genders. However, Male students have more than the average attitude level, and females have attitudes lower than males. While analyzing the age group, graduates between 19 and 22 age group have an average level of attitude, while those above 26 age group have more. While analyzing the place of residence, rural students have high levels of attitude than urban students. The analysis shows that Science students have a low level of attitude, while Arts and Technical students have high levels of attitude. Among the family types, the P value is (0.000*) lesser than 0.050. A 1% significant difference is found among the family types. Students from nuclear families have low-level attitudes, while students from joint and separated families have high levels of attitude. Students from families who have an income of 1 lakh have more of a high-level attitude, while families who have three lakhs have more of a low level of attitude. Among the locations of the colleges, the P value (0.035) is lesser than 0.050; there is a 5% significant difference found among the college location. Students from Urban areas have a low-level attitude towards entrepreneurship, and rural graduates have high levels of attitude.
GENERAL FINDINGS
ANOVA (Test of difference)
The Annova test on differences indicates that 1% significant differences are established among the independent variables such as Subjects studied (0.002*), Family types (0.000), and Family annual income (0.001*). A 5% level of significant differences among the College locations is established. No significant differences were found among the variables: Gender, Age, Education, Communities, College types, Residences, and Generations of study.
CHI SQUARE (Test of association)
The chi-square test proves that a 1% level of association exists between the variables Subjects (000*), Family types (001), Annual income (000), and a 5% level of association exist between College locations (035) with the overall entrepreneurship attitude. The association is not established with Genders, Age, Community, Education, College types, Residence, and Generation of study with the overall entrepreneurship attitude.
CORRELATION (Test of relationship)
The Correlation test proves that a 1% level of association exists between the variables Subjects (001*), College locations (010), Family type (000), Annual income (000), and a 5% level of association exists between Generation of study (033) with the overall entrepreneurship attitude. The association is not established with Gender, Age, Community, Education, College types, and Residence with the overall entrepreneurship attitude.
DISCUSSIONS
Entrepreneurs are the driving forces of creating a revival in the economy. This study unveils three essential factors. In India’s higher education institutions, entrepreneurial education has grown significantly. It positively affects the entrepreneurship attitude of graduates in colleges. The study reveals that graduates are enlightened with knowledge and intention of entrepreneurship due to education obtained in the universities. A state-wide gap exists concerning equipping the younger generation with entrepreneurial education and training. Educational institutions should create an environment that is supportive of entrepreneurial activities. On the other hand, today’s youth are not interested in blue-collar jobs. Awareness and skill training play a vital role in developing these skills. Future research should explore an understanding between training and skill development and their causal relations from various industries. This limited sample size, lack of awareness of entrepreneurship policies, employability skill training schemes, and programs should be taken up in future research. The government should prioritise providing e-learning resources as there is an increasing need to bridge skill gaps. The government can include e-learning resources’ courses into academic institutions’ curricula.
On the other hand, we see that the country is dealing with a number of issues, including a lack of qualified trainers and an imbalance between the supply and demand of a trained labour force. Our workforce will be challenged by the fourth and fifth industrial revolutions, which are currently under way. The government should support projects to offer skill development throughout regional hubs of our nation (Cabral & Dhar, 2019). For a company to achieve its goals, human reskilling is essential (Sultana, 2022). Human capital development is urgently needed and requires reinventing, retooling, and reskilling (3Rs). After the disastrous consequences of the COVID-19 epidemic, it is an efficient approach to revive the economy (Raimi, 2021).
CONCLUSION
Today’s youth are the backbone of future India. Entrepreneurship attitude with all its aspects among the college youths in Kurukshetra and Kaithal is only average level. There is a need to reconsider policies at the state and institutional levels to achieve the goals of vision India 2047. So Human reskilling is extremely necessary for employees, employers, and the government. The Govt of India should set up numerous skill training and development centers to bridge the skill gap and the shortage of skilled labor force.
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