Career Preferences and Entrepreneurial Orientation among Undergraduate Female Agricultural Students 

The agriculture and allied sectors provide livelihood support to 42.3 per cent of population and contribute 18.2 per cent to the GDP of India (Anonymous, 2024b). The availability of quality human resources is crucial for development of any sector in an economy. The human resource development required for the agriculture and allied sectors of India occurs mostly in the government colleges. At present, there are 66 State Agricultural Universities, 4 ICAR Deemed Universities, 3 Central Agricultural Universities and 4 Central Universities with Agricultural Faculty in India. Besides, many affiliated private colleges are also offering the agricultural courses.

The bachelor of science in agriculture is a 4-year degree available to 10+2 students with science stream in India. Around 32464 agricultural graduates are passing out every year in India (Anonymous, 2024a). Only very few of them are landing in public sector employment and the unemployment rate is high among the agricultural graduates (Mahra et al., 2015) due to meager job opportunities in the private sector and the high annual output of graduates with an increase in the number of seats and colleges, both government and private. To combat this unemployment, the government of India is implementing the Agri-Clinics and Agri-Business Centres scheme to promote establishment of agri-clinics/agri-business centres by the unemployed agricultural graduates. Khan (2024) reported that many states and union territories had a female participation ratio of more than 50% in UG courses in agriculture. Indian women can have a greater role in establishing secondary agricultural related enterprises (Ponnusamy et al., 2020). The context of increasing number of female students enrolling in agriculture and allied courses and high unemployment rate among the agricultural graduates present a need for women centric studies of career preferences and other aspects like entrepreneurial orientation. The fact that around 52% of agricultural students are from rural background (Thammi-Raju et al., 2022) demands studies to know the effect of students’ background on their career choices and entrepreneurial orientation. The present study was aimed at studying career preferences of undergraduate female agricultural students to identify what they enjoy doing and what are the factors influencing their career preferences and assessing their entrepreneurial orientation to understand their readiness for entrepreneurship and constraints perceived by them to pursue a career in entrepreneurship which may provide valuable information for policy formulation to combat unemployment and promote agricultural enterprises in India.

The present study was conducted on 90 final-year female agricultural students selected equally from government and private agricultural colleges of Andhra Pradesh at the ICAR-National Institute for Research on Commercial Agriculture-Krishi Vigyan Kendra, Kalavacharla in the year 2024. The descriptive research survey was employed to collect data from the students, who were requested to fill out printed copies of the survey document, which was specifically designed to meet the objectives of the study. The responses from each student were entered into Microsoft Forms to collate the information and for further analysis. 

The basic details such as background (urban and rural), family type (joint and nuclear), family size, number of siblings, educational qualifications of family members, choice towards higher education, attitude of family towards starting a new enterprise and preferred enterprise were also obtained from the respondents along with the information regarding career preferences and factors influencing them, entrepreneurial orientation and constraints in pursuing an entrepreneurial career.

The choices with respect to educational qualifications such as illiterate, primary school, secondary school, intermediate, graduation and post-graduation were given 0, 1, 2, 3, 4 and 5 scores, respectively. Family education score of every respondent was obtained by summing the scores of her family members and the mean family education score was calculated using the following formula:
 

 

 
The correlation analysis was conducted to assess the relationship among basic parameters such as background, family type, family size, number of siblings, family education score, family income and choice of higher education.

 A set of 16 career options (10 in government sector and 6 in private sector) relevant to the agricultural students were rated on a 4-point Likert scale (Highly preferred-4, Preferred-3, Least preferred-2, Not preferred-1). The Weighted Mean Score (WMS) for each career choice was calculated by using the below formula. Based on the Weighted Mean Scores, ranks were assigned to the career options using simple rank order technique.
 

A list of 7 factors responsible for the choice of career were rated on a 5-point scale (Very important- 5, Fairly important- 4, Important- 3, Least important- 2, Not at all important- 1) and ranks were assigned based on Weighted Mean Scores calculated in the same manner as that of career preferences.

The Mann-Whitney U test was conducted to know the effect of background (rural and urban) on career preferences and the factors involved in deciding them.

The entrepreneurial orientation assessment was done based on the attributes such as self-confidence and risk-taking ability of the students. Each statement under an attribute had been given 5 options (Strongly agree, Agree, Un-decided, Disagree, Strongly disagree) with scoring pattern of 5, 4, 3, 2 and 1 respectively for positive statements, which was reversed in case of negative statements. Score for an attribute is obtained using the below formula as per Ntow et al., (2023). The Entrepreneurial Behavioural Index (EBI) was also calculated in the same manner combining all the statements under the 2 attributes.
 

The correlation analysis was used to assess the association of basic parameters with metrics of entrepreneurial orientation such as self-confidence score, risk taking ability score and EBI. The Multiple Linear Regression analysis was used to develop a model for prediction of Entrepreneurial Behaviour Index (EBI).

A set of 13 constraints (8 are related to individual/intrinsic and 5 are related to local business environment/extrinsic) were analysed through the Garett’s ranking technique which involves asking the students to rank the constraints and the calculation of percent positions from the order given by each student using the formula given below. The percent positions were converted into scores as per the table given by Garett and Woodworth (1969). The mean score for a constraint was obtained by adding the scores of the individual respondents and dividing the sum with number of respondents who perceived the constraint. The constraints were ranked based the mean scores.
 

 

 
Where,
R_ij = Rank given for i^th constraint by j^th individual.
N_j = Number of constraints perceived or ranked by the j^th individual.

Basic information
 
The present study revealed that most of the students participated in the survey were from urban background (58%), nuclear families (87%) with below 5 members (89%). Majority of their families had family education score in the range of 2-4 and annual family income in the range of 2-4 lakh rupees. The result regarding background was in agreement with those of Yadav and Kashyap (2017). The result of the present study with respect to family type coincided with that of Shekhar et al., (2016); Jayasudha and Sheela (2021) and Vijayalakshmi et al., (2022), while the results regarding family size and family education were similar to those of Ramesh (2016). Regarding higher education, most of the students participated in the present study were inclined to pursue post-graduation courses (53%) and remaining were not pursuing higher education after UG due to various reasons such as desire to earn money by joining a job (27%), lack of financial support from family (13%), lack of acceptance of family (5%) and reason of believing that it is waste of time to pursue higher education as there are no suitable jobs (2%). These results conformed to those of Chaudhary et al., (2023). Majority (58%) of the students’ families were not favourable to start a new enterprise which is contrary to the findings of Ramesh (2016). Among the enterprises listed, most of the students were inclined towards establishing a nursery (20%). However, Orabi et al., (2022) determined that post-harvest management was the most preferred enterprise among rural agricultural students. This disagreement might be due to the fact that prospective enterprises vary according to local conditions.

The correlation coefficients among some parameters related to basic information such as background, family type, family size, number of siblings, family education score, family income and planning for higher education were given in Table 1. The background had significant (P<0.01) positive association with family education score and family income which clearly indicates that students from urban background had significantly higher family education score and family income than those from rural background. The reason for the significant negative association of family type with family size and number of siblings might be that the nuclear families had lower number of members and siblings than the joint families. The increase of family size with siblings was the probable reason for the significant positive association of family size with number of siblings. Table 1 shows that the family income and planning for higher education had significant (P<0.01) positive association with family education score. It can be deduced from this result that educated families had more income and students from high income families had more chances of getting higher education.


 
Career preferences
 
The results obtained from the analysis of career preferences of the students participated in the present study were depicted in Table 2. The present study revealed that the Food Safety Officer followed by the Agricultural Officer were the most preferred careers among the students participated in the survey. Becoming entrepreneur or Marketing Development Officer in seed companies was the third most preferred career. The scientist under ICAR followed by Bank Manager in public sector or Marketing Development Officer in fertilizer companies were the fourth and fifth most sought career options by the students. Chaudhary et al., (2023) supported these results. However, Balan (2003) reported that the most preferred careers were administrative service and bank job for female agricultural graduates and Akhila and Mankar (2021) determined that Assistant Professor was the most preferred career. The fact that the career planning is very dynamic process and is influenced by many factors might be the probable explanation for these discrepancies. It can be inferred from the Table 2 that there were no significant differences between the rural and urban students in terms of their career choices which indicates that background of a student had no influence on her career planning. Contrary to this, Lakshmi et al., (2011) reported significant relationship between background and career preferences of agricultural students.


 
Factors responsible for career preferences
 
In general, various factors such as intrinsic interest in work, job security, salary, status of job, job satisfaction, work environment and work-life balance play a role in decision making towards career preferences. The ranking and analysis of the factors involved in deciding the career preferences was presented in Table 3. The present study revealed that job security followed by intrinsic interest in work and job satisfaction were the most deciding factors for career preferences among the female students participated in the survey. These results were in agreement with those of Ramesh et al., (2019). Table 3 shows that the Weighted Mean Scores of intrinsic interest in work, job satisfaction and work environment for urban students were significantly higher than those for rural students which indicates that the students from urban background are more particular about good conditions of employment than the students from rural background.


 
Entrepreneurial orientation
 
The self-confidence and risk-taking ability are the two important attributes of entrepreneurial orientation from which an Entrepreneurial Behavioural Index (EBI) can be constructed. The mean scores of self-confidence, risk-taking ability and Entrepreneurial Behavioural Index (EBI) were 0.80±0.01, 0.69±0.01 and 0.73±0.01 respectively, which suggest that the students were high in self-confidence and medium in terms of risk-taking ability and entrepreneurial behavioural index. Many authors such as Jayasudha and Sheela (2021) and Yadav and Kashyap (2017) observed similar results.

The correlation coefficients between parameters of basic information and entrepreneurial orientation were presented in Table 4, a perusal of which tells that the self-confidence (P<0.01) and risk-taking ability of students improve with increase in number of family members. It is very interesting to note the finding of the present study that the self-confidence (P<0.01) and risk-taking ability had inverse relationship with the family education score. The present study revealed that the Entrepreneurial Behavioural Index (EBI) was significantly more in case of students from families of joint type, families with large number of members and low education scores. The results are indicating the reluctance of students from highly educated nuclear families to venture into entrepreneurship. The influence of demographic factors such as family background, size and type on students’ entrepreneurial behaviour was also found by Behera and Raj (2024).



Based on significant correlations between EBI and basic parameters, the regression equation [EBI = 0.800 - 0.023 (Family type) + 0.011 (Family size) -0.024 (Family education score)] was evolved which is a statistically significant (P<0.05) model and can be used for prediction of EBI but with less accuracy (R₂ = 0.131) which is very common in social or behavioural sciences. The relationship between actual values of dependent variable (EBI) and its predicted values obtained through the regression model was depicted in Fig 1.


 
Constraints in pursuing a career in entrepreneurship
 
The results of analysis of constraints perceived by the students were presented in Table 5. The Garett’s ranking technique determined that the fear of loan followed by insecure income, excessively irregular working hours and lack of suitable attitude for entrepreneurship were the four major constraints perceived by the students in opting for a career in entrepreneurship. It is noteworthy that all the four major constraints were intrinsic and the same were the four major constraints for rural students too. The insecure income followed by fear of loan, excessively irregular working hours and tough competition were the four major constraints perceived by the students from urban background. The results suggest the need of a robust entrepreneurial education to promote entrepreneurship among the agricultural students. The results were almost similar to those of Patel et al., (2020) and Ramesh (2016). Conversely, Srishailam et al., (2021) noted that lack of infrastructure was the major constraint among agricultural entrepreneurs. The lack of practical knowledge on entrepreneurship was reported as the major constraint among agriculture students by Shaik and Khandave (2020). Therefore, it can be suggested that the management of agricultural colleges need to be focussed on imparting practical knowledge to their students.


 

Based on the results, it can be concluded that the female agricultural students had higher family education score, family income and more chances of getting higher education if they are from urban background, they prefer government jobs such as food safety officer and agricultural officer, the job security is the most important factor involved in deciding their career, they are high in self-confidence and medium in terms of risk-taking ability and Entrepreneurial Behavioural Index (EBI), their EBI increases with an increase in number of family members and also with a decrease in family education score and the fear of loan was the major constraint perceived by them in pursuing an entrepreneurial career.

The present study was supported by the ICAR-National Institute for Research on Commercial Agriculture (formerly ICAR-CTRI), Rajahmundry.
 
Disclaimers
 
The views and conclusions expressed in this article are solely those of the authors and do not necessarily represent the views of their affiliated institutions. The authors are responsible for the accuracy and completeness of the information provided, but do not accept any liability for any direct or indirect losses resulting from the use of this content.
 
Informed consent
 
No approval of committee of experimental animal care was required to accomplish the goals of this study.

The authors declare that there is no conflict of interest regarding the publication of this article. No funding or sponsorship influenced the design of the study, data collection, analysis, decision to publish, or preparation of the manuscript.