Modeling drivers for successful adoption of green business: an interpretive structural modeling approach

Like most other developing countries, Bangladesh is facing tremendous pressure to mitigate climate change effects and prior environmental degradation, further creating a vulnerable condition in mitigating its environmental, social, and economic circumstances. Green business approaches could be one of the better weapons for these severe conditions as they quantify the incorporation of environmental and social concerns without compromising economic development. They have gained considerable attention from governments, industries, and researchers over the past few years. The main aim of this paper is designed to build up a structured model (interpretive structural modeling) of drivers for adopting green business (GB) in the context of emerging economies. The interpretive structural modeling (ISM) will allow the assessors in the regulatory, market, and other sectors to promote the smooth utilization of green business strategies by defining and recognizing the linkages among the drivers associated with the green business. The driver’s intimate relationship enables a hierarchy by compiling their dependence and driving power. For demonstrating the structural modeling for the identified drivers, we used combined “Matriced' Impacts Croisés Multiplication Appliquée á un Classement” (MICMAC) analysis and ISM model for characterizing the drivers as indicated by their driving and dependence power. Throughout, the evaluation of the available literature followed by a discussion with experts (both industrial and academic) was done for the identification of the drivers for green business adoption. A structured model (ISM) and MICMAC (as fuzzy analytical tools) analysis are required to give a boon set of knowledge to the assessors of the legislature and business industry, which further lead them for resource maximization in a sustainable way to embrace green strategies into their core business process.