Bhaskar Bhowmick

Innovation Network for Entrepreneurship Development in Rural Indian Context: Exploratory Factor Analysis

Innovation has been considered as one of the key drivers of economic development for any nation. In the rural context, the innovation concept is applied with the intention to determine new ways to solve traditional and emerging problems that the rural people face. The innovation network concept has in the rural context become extremely important because it assists to complement scarce resources and create new opportunities for rural development base by establishing a relationship between rural actors with other actors. Thus, the main purpose of this paper is to identify variables of innovation network and to conceptualize innovation network in the rural context. The study has been executed through a field survey of the rural entrepreneurs, through interviews and closed ended questionnaires in rural regions of Gujarat in India. This paper has used exploratory factor analysis in order to investigate factors that might explain the underlying belief of rural entrepreneurs about innovation networks. The paper finds out three factors, namely: (a) innovation network with a private organization, (b) innovation network with NGOs, and (c) innovation network with public organizations. The finding of this study revealed that production enhancement, information accessibility, skill development and entrepreneurial opportunities are considered the most important criteria for conceptualization of innovation network in the rural context. This study allows for implications to be made for rural entrepreneurship development and policy formation. In future research there remains the scope to incorporate larger sample data, greater number of variables of innovation network and conduct the study in other countries.

Does technology transfer training concern for agriculture output in India? A critical study on a lateritic zone in West Bengal

Purpose The purpose of this paper is to explore and identify the indicators of institutional barriers hindering the technology transfer training (TTT) process behind the technology adoption lag affecting the agricultural output in India through development of a scale. Design/methodology/approach Quantitative technique has been followed for data collection through a close-ended questionnaire scored on the seven-point Likert scale. The sample size was considered as 161; target respondents were farmers and farmer-centric individuals. Data were analyzed using an exploratory factor analysis technique. Findings Factor analysis revealed that there are three significant factors related to TTT process, namely, comprehension, customization and generalization, which are liable for institutional barriers in technology adoption by farmers. Research limitations/implications The main limitation is biasness from both respondents’ end and interviewer’s end might exist during survey due to differences in perception. Social implications The key beneficiaries from this research are the small and marginal farming community in India. They can enhance their productivity through an appropriate training process. Corporates will show interest in investment through the mechanism of corporate social responsibility. Originality/value Under this study, the factors of the institutional barriers from the farmers’ perspective are being introduced as a new research contribution, especially for the resource crunch area of Jangalmahal and other similar places in India.

Architecture of Tertiary Healthcare Delivery Model for Sub-Urban/Rural India

Healthcare facilities are extremely fragmented and less affordable across much of the developing world. Business architecture for healthcare systems is one of the vital requirements to bridge the gap in developing countries. The resource needed to suffice the insufficiencies of the current health system needs an algorithm driven process. This paper is an attempt to design such an algorithm for resource sharing and utilization. An empirical study has been done to check the satisfaction determinants of the patients using regression analysis.