Does Career Planning Drive Agri-entrepreneurship Intention Among University Students?:
20 Nov 2020-Global Business Review (SAGE PublicationsSage India: New Delhi, India)-pp 097215092096126
TL;DR: In this article, the apathy of rural youth to engage in agriculture as their profession was tested across five universities in eastern India on a sampled data set, and the results showed that rural youth are apathetic to agriculture.
Abstract: The rationale behind this study is to test the apathy of the rural youth to engage in agriculture as their profession. This research was conducted across five universities in eastern India on a sam...
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25 May 2023
TL;DR: In this article , structural equation modeling (SEM) and artificial neural networks (ANN) were employed to determine the variables that were linked to university students' intentions to pursue agricultural-related employment.
Abstract: Abstract The study's goal was to determine the variables that were linked to university students' intentions to pursue agricultural-related employment. Quantitative data was gathered from 323 students who were enrolled in various agricultural-based university programs in Bangladesh. Structural equation modeling (SEM) and artificial neural networks (ANN) were employed to examine the data. The results revealed that students' intentions to enter agricultural-related careers were predicted by their attitudes toward agriculture, agricultural knowledge, perceived behavioral control, facilities and resource conditions, innovativeness and creativity, career planning, perception of sustainable agriculture methods, perception of organizational support, and technological competency. Perceived behavioral control is the strongest predictor. Subjective norms, perceived value, and entrepreneurial capabilities were found the insignificant predictors. The results shed light on the parameters agricultural undergraduates take into account when selecting whether to pursue jobs in the field of agriculture. This can assist academic specialists in retaining and attracting students by meeting their demands for motivation. By including nine extra components, the study broadens the theory of planned behavior's application for predicting intention in the agricultural sector. The study first time examined the linear and nonlinear correlations among variables. The areas where programming efforts are most likely to be successful can be more clearly identified by having a deeper grasp of the variables that influence students' decisions regarding their future professions in agriculture.
TL;DR: In this article , structural equation modeling (SEM) and artificial neural networks (ANN) were employed to determine the variables that were linked to university students' intentions to pursue agricultural-related employment.
Abstract: The study's goal was to determine the variables that were linked to university students' intentions to pursue agricultural-related employment. Quantitative data was gathered from 323 students who were enrolled in various agricultural-based university programs in Bangladesh. Structural equation modeling (SEM) and artificial neural networks (ANN) were employed to examine the data. The results revealed that students' intentions to enter agricultural-related careers were predicted by their attitudes toward agriculture, agricultural knowledge, perceived behavioral control, facilities and resource conditions, innovativeness and creativity, career planning, perception of sustainable agriculture methods, perception of organizational support, and technological competency. Perceived behavioral control is the strongest predictor. Subjective norms, perceived value, and entrepreneurial capabilities were found the insignificant predictors. The results shed light on the parameters agricultural undergraduates take into account when selecting whether to pursue jobs in the field of agriculture. This can assist academic specialists in retaining and attracting students by meeting their demands for motivation. By including nine extra components, the study broadens the theory of planned behavior's application for predicting intention in the agricultural sector. The study first time examined the linear and nonlinear correlations among variables. The areas where programming efforts are most likely to be successful can be more clearly identified by having a deeper grasp of the variables that influence students' decisions regarding their future professions in agriculture.
TL;DR: In this article , an emerging meta-theoretical process framework in the form of Manuel Delanda's assemblage theory is applied to extend our knowledge of how entrepreneurial intention (EI) unfold over time.
Abstract: Contemporary research has shown that entrepreneurial intention (EI) has become an increasingly popular topic of investigation. That being said, whereas the parent field of entrepreneurship is acknowledging its inherent dynamic and processual nature, the same is not true of EI. The current article therefore seeks to apply an emerging meta-theoretical process framework in the form of Manuel Delanda’s assemblage theory (AT) in ambition to extend our knowledge of how EIs unfold over time. A single in-depth case study design was implemented to track changes in an individual’s entrepreneurial intending. Data were captured using semi-structured interviews and then analysed using NVivo coding software. Findings suggest that it is through the interaction of contextually defined factors and their unique capacities that an emergent intentional whole can be created. The current article provides a foundation to consider intent through a more socially situated outlook and can act as a platform to guide further research in the area. The concept of entrepreneurial process intentions is introduced to atone for the dynamic interplay between spatially and temporally bound factors that can lead to a specific form of EI emerging.
TL;DR: Based on the ConvMF algorithm, this article proposed an entrepreneurial project recommendation algorithm based on a deep neural network and matrix decomposition, which can constantly adjust the recommendation results according to the real-time behaviors of users.
Abstract: The recommendation system is an active, personalized, and real-time technology platform proposed in the 1990s to solve the problem of information overload. The recommendation system can constantly adjust the recommendation results according to the real-time behaviors of users. In other words, if the user’s interest changes, the recommendation system can present different information to the user. Therefore, the recommendation system is the best way to solve the problem of information overload in entrepreneurial projects. Based on the ConvMF algorithm, this paper proposes an entrepreneurial project recommendation algorithm based on a deep neural network and matrix decomposition. A deep neural network was established for the extraction of the hidden features of entrepreneurial projects, and a convolution neural network was used to process the text description information of entrepreneurial projects. One-hot coding was used to process the regional characteristics and financing round characteristics of entrepreneurial projects, and word embedding was used to process the label features of entrepreneurial projects. The implicit features of users are extracted from the user’s rating matrix using matrix decomposition technology. Finally, recommendations are made according to the implicit characteristics of users and the items learned.
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TL;DR: Ajzen, 1985, 1987, this article reviewed the theory of planned behavior and some unresolved issues and concluded that the theory is well supported by empirical evidence and that intention to perform behaviors of different kinds can be predicted with high accuracy from attitudes toward the behavior, subjective norms, and perceived behavioral control; and these intentions, together with perceptions of behavioral control, account for considerable variance in actual behavior.
65,095 citations
TL;DR: In this article, structural equation models with latent variables are defined, critiqued, and illustrated, and an overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence.
Abstract: Criteria for evaluating structural equation models with latent variables are defined, critiqued, and illustrated. An overall program for model evaluation is proposed based upon an interpretation of converging and diverging evidence. Model assessment is considered to be a complex process mixing statistical criteria with philosophical, historical, and theoretical elements. Inevitably the process entails some attempt at a reconcilation between so-called objective and subjective norms.
19,160 citations
TL;DR: The authors examines recent developments in the role of the university in increasingly knowledge-based societies and concludes that the ''entrepreneurial university'' is a global phenomenon with an isomorphic developmental path, despite different starting points and modes of expression.
2,345 citations
TL;DR: In this paper, the authors conducted a quantitative review of the literature and found that there is indeed support for the value of entrepreneurship education and training (EET) in the context of human capital theory and found a significant relationship between EET and entrepreneurship-related human capital assets.
1,043 citations
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TL;DR: In this article, the authors analyzed the impact of a leading entrepreneurship education program on college students' entrepreneurship skills and motivation using an instrumental variables approach in a difference-in-differences framework.
Abstract: This paper analyzes the impact of a leading entrepreneurship education program on college students’ entrepreneurship skills and motivation using an instrumental variables approach in a difference-in-differences framework We exploit that the program was offered to students at one location of a school but not at another location of the same school Location choice (and thereby treatment) is instrumented by the relative distance of locations to parents’ place of residence The results show that the program does not have the intended effects: the effect on students’ self-assessed entrepreneurial skills is insignificant and the effect on the intention to become an entrepreneur is even negative
1,021 citations