Analysis of enablers for vertical integration to enhance rural employability

Abstract

Purpose The purpose of the paper is to identify, analyze and select the enablers for vertical integration of Aloe vera supply chain (AVSC) so that rural employability will be enhanced in the context of Rajasthan, India. Design/methodology/approach Interpretive structural modeling (ISM) was proposed to develop a structural model to identify the right enablers for enhancing the rural employability and business prospects. Also, fuzzy-matrix cross-reference multiplication applied to classification (F-MICMAC) was applied to segregate the enablers into four clusters on the basis of their driving and dependence power. Finally, the significant enablers were selected. Findings Out of identified 13 enablers, three enablers (i.e. institute for training and research, transportation infrastructure and government incentives for value addition) were appearing at the bottom of the ISM structural model and also in the driving quadrant of driver-dependent diagram. Therefore, they are the significant enablers for vertical integration of AVSC to enhance the rural employability in the context of Rajasthan, India. Research limitations/implications The interactions among enablers are not statistically validated. However, the empirical analysis and total interpretive structural modeling may be used for this purpose. Practical implications The outcomes of the study will provide the guidelines for implementation of vertical integration at the village level to enhance rural employability in the context of Rajasthan, India in specific. Originality/value Although a few studies have been reported in the literature related to value-addition process (vertical integration), but the modeling of enablers to segregate and identify the appropriate enablers for vertical integration of AVSC for enhancing employability at the rural areas is unique.