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Article
Publication date: 2 February 2024

Ravita Kharb, Charu Shri and Neha Saini

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies…

Abstract

Purpose

The objective is to develop an empirical model estimating the relationship and interaction amongst the factors affecting and enhancing green finance (GF) in developing economies like India.

Design/methodology/approach

Around nine growth-accelerating enablers of green financing were found through literature and unstructured interviews and analysed using the total interpretive structural modelling (TISM) method. The hierarchical link between each factor is established using TISM, and further to evaluate the driver-dependent relationship the Matriced’ Impacts Croises Appliquee Aaun Classement (MICMAC) approach is utilised.

Findings

The findings demonstrate an interrelationship between growth-accelerating factors, where the political environment and information and communication technology (ICT), have minimal dependency but a strong driving force. Political environment and ICT are found as strategic-level factors lying at the bottom of the model driving towards the dependent variables. The government should focus on enacting effective policies such as the green credit guarantee scheme and carbon credit and establishing a regulatory framework to enhance green financing.

Research limitations/implications

This study examines the literature to generalise the findings and focus on the primary motivators for developing green financing. To increase green financial activity, practitioners must concentrate on aspects with significant driving forces. Furthermore, it makes organisations more profitable, efficient and competitive and promotes long-term growth.

Originality/value

The study is the first in the literature which identifies the growth-accelerating factors of green financing using the TISM and MICMAC-based hierarchical models.

Details

Kybernetes, vol. ahead-of-print no. ahead-of-print
Type: Research Article
ISSN: 0368-492X

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