Evaluating the Indian retail service quality enablers using interpretive structural modelling

Rema Gopalan, Sreekumar and Biswajit Satpathy

International Journal of Business Performance Management, 2016, vol. 17, issue 4, 365-393

Abstract: Indian retail as one of the major sub-sectors in services industry is going through a transition phase. In such context, the proposed research aims to provide a comprehensive framework for the various important retail enablers in India. A combined approach of interpretive structural modelling and fuzzy MICMAC is adopted to identify and classify the key enabling factors based on their direct and indirect relationship. Based upon the literature survey and expert opinion 13 key enabling factors have been identified. Thirteen identified factors are government policies/regulations, supply chain, management commitment, location of store, image of the store, consumer culture, availability of skilled manpower, technology adoption, globalisation/competition, product localisation, real estate/infrastructure, workforce management and value conscious consumers. The MICMAC analysis reveals that four of these factors can be classified as independent, three factors as linkage and six factors are classified as dependent. However no factor is classified as autonomous. The fuzzy MICMAC shows that four factors can be classified as independent, nine factors as linkage and no factor is classified as autonomous and dependent. Based on this classification companies can devise marketing strategies across the retail value chain to become successful.

Keywords: ISM; FMICMAC; retail industry; fuzzy MICMAC; India; service quality; interpretive structural modelling; services; service industry; government policy; government regulation; supply chain management; SCM; management commitment; store location; store image; consumer culture; skilled manpower; technology adoption; globalisation; competition; product localisation; real estate; infrastructure; workforce management; value conscious consumers; marketing strategies; retail value chain. (search for similar items in EconPapers)
Date: 2016
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