یک روش فازی مولتی گرید PCA-AHP ترکیبی برای ارزیابی انعطاف پذیری مبتنی بر بازاریابی A hybrid PCA-AHP-Multi-grade Fuzzy approach to assess marketing-based flexibility

1. Introduction Business firms competing in today’s hyper competitive uncertain environment need to develop a market-driven approach (Filieri, 2015). Since market-driven organisations largely depend on their ability to respond quickly and effectively (Didonet et al., 2012), flexibility becomes one of the important capabilities to compete in the market. In manufacturing literature, flexibility is classified into manufacturing-based flexibility and marketing-based flexibility (Chen et al., 1992). Marketing-based flexibility directly affects market orientation of the firm and represents the outcome of manufacturing-based flexibility; therefore, it is important that a firm must develop marketing-based flexibility to improve its competitive position. Further, considering the major role of marketing-based flexibility in competitiveness, it is essential to assess existing flexibility of a firm. Despite the widespread importance of marketing-based flexibility, majority of the studies is limited to manufacturing-based flexibility (Chuu, 2005) and there are few studies that assess how firms develop marketing-based flexibility to compete in the marketplace. Although, a variety of approaches, such as EFA (Koste et al., 2004), G theory (Malhotra and Sharma, 2008), analytical hierarchical process (AHP) (Mishra et al., 2017), fuzzy set theory (Chuu, 2005; Das and Caprihan, 2008) have been used to quantify and assess single or multiple dimensions of flexibility, studies have not been done to assess marketing-based flexibility in terms of its source factors. Since marketing-based flexibility is determined by the flexibility of its source factors, it is important to assess marketing-based flexibility in terms of its source factors. To address this gap, the aim of the study is threefold: first, it identifies important factors that influence marketing-based flexibility in firms; second, it aims to develop a marketing-based flexibility index to assess the existing flexibility level in firms; third, it attempts to highlight the weak areas that should be taken care to improve the flexibility level in firms. This study proposes a hybrid approach to assess marketing-based flexibility and demonstrate the application of the approach in Indian apparel firms. Indian firms are selected mainly due to following reasons: flexibility implementation practices are considerably low in India (Mishra et al., 2017); compared to developed nations, Indian firms give highest priority to quality and least priority to flexibility (Dangayach and Deshmukh, 2005); adoption of advanced manufacturing technologies (AMTs) at shop-floor level is really low and Indian firms give more emphasis on simple, standalone and less capital intensive AMTs compared to AMTs, which require considerable investments and demand integration among different technologies (Thakur and Jain, 2008). The rest of the paper is structured as follows. In Section 2, background literature is provided. Section 3 describes research methodology and Section 4 presents results of principal component analysis (PCA). Section 5 illustrates marketing-based flexibility assessment model and Section 6 presents discussion and managerial implications of the study. The conclusion, limitations and future scope are described in Section 7.