Identification of Green Procurement Drivers and Their Interrelationship Using Fuzzy TISM and MICMAC Analysis

Identification of Green Procurement Drivers and Their Interrelationship Using Fuzzy TISM and MICMAC Analysis

Surajit Bag (Tega Industries South Africa Pty Ltd., South Africa)
Copyright: © 2018 |Pages: 17
DOI: 10.4018/978-1-5225-2255-3.ch270


The objective of the current study is to identify the leading green procurement drivers and identify the interrelationships using fuzzy total interpretive structural modeling and MICMAC approach. For the purpose of this study, twenty-five drivers were identified from existing literature which influences green procurement practices and finally refined through experts' opinion. The final fuzzy model consists of fuzzy relationships between one to one criteria. The key drivers which emerged from Fuzzy TISM and MICMAC analyses are Government policy and Regulations, Total Quality Environmental management, Management Support, Management Review, Continuous education of employees, Cross functional team building, Organization Culture, and Green process and Technology. The green procurement model may assist supply chain practitioners in better decision making and successful implementation of green procurement programs.
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In this section an attempt has been taken to briefly explain the key drivers of green procurement.

Government Policy and Regulations

Governments are among the largest consumers in an economy. The public sector on average spends 45%-65% of their budgets on procurement. Given this substantial purchasing power, governments have enormous leverage to stimulate and drive markets for sustainable production and consumption when they make a determined effort to purchase ‘green’ products and services. Adopting such an approach is a smart form of procuring goods and service – it not only improves the efficiency of public procurement but also uses the public market power to bring about significant environmental and socioeconomic benefits. Supply chain management operates within a regulatory framework set by National Government and extended by provinces and local governments to specific policies, legislation and regulations. In South Africa for instance important legislation influencing this function includes the Public Finance Management Act (1999), Preferential Procurement Policy Framework Act (2000), Preferential Procurement Framework Regulations (2001) and National Treasury Regulations (2005). The Municipal Finance Management Act (MFMA) of 2003 governs the financial and supply chain management functions of Local Government. In developing green procurement policies, local government would need to ensure that these policies: are aligned with their existing Supply chain management regulatory frameworks; avoid a clash between the Preferential Procurement regulations and environmental principles or criteria in the policy; incorporate green procurement in all dimensions of the supply chain management cycle; and institutionalize green procurement within the existing structures set out by the regulatory framework. Government policy and regulations positively influences green procurement (Min & Galle 1997; Diabat & Govindan 2011; Hassini et al., 2012; Bag., 2014; Appolloni et al., 2014)

Key Terms in this Chapter

Green Procurement: Green Procurement is procuring of products and services that cause minimal adverse environmental impacts. It incorporates human health, social and environmental concerns into the search for high quality products and services at competitive prices.

Total Interpretive Structural Modeling (TISM): Fuzzy TISM is an extension of Interpretive structural modeling (ISM) technique. ISM methodology, transforms unclear, poorly articulated models of systems into clear, well-defined models. ISM uses experts to judge the variables, and the relations among the variables are interpreted. ISM depends on the experts’ knowledge and familiarity with the firm, its operations, and its industry. ISM generates deep knowledge of the subject and is greatly helpful for practitioners.

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