Interpretive multi-criteria valuation of flexibility initiatives on direct value chain

Abstract

Purpose Activities on direct value chain directly add value to the products/services delivered to the customers. This value addition can be further enhanced by taking up flexibility initiatives on these direct value chain activities. The purpose of this paper is to identify flexibility initiatives on the direct value chain and carry out their valuation. Design/methodology/approach Since different value addition criteria (i.e. benefits and costs) may be both tangible and intangible, an interpretive valuation based on multi-criteria framework would be desirable. The paper deploys the efficient interpretive ranking process (IRP) for this purpose. It uses total interpretive structural modeling (TISM) to derive weights of criteria based on their respective driving power. The paper also makes a methodological contribution to assess transitive dominance in IRP based on transitivity check as used in the modified TISM process. Findings The paper uses a multi-criteria valuation to examine the proposition that the flexibility initiatives will add a higher value as we go downstream in the value chain. The flexibility initiatives linked with marketing such as product upgradation and switching, customized services and dynamic pricing are found to be most value adding in character. Research limitations/implications The main limitation of this study is that it is generic in nature and need to be replicated in multiple case situations. The methodology proposed can be utilized for specific case analysis for flexibility valuation on the direct value chain. Practical implications The practitioners may be able to use the proposed method of TISM–IRP with improvements in real-life applications. The proposed multi-criteria valuation is interpretive in nature and can be utilized by practicing managers in group settings even if they do not have complete data. Originality/value The strategy and operations researchers will find promise in the methodology to investigate and prioritize the initiatives planned to enhance flexibility in different value chain activities. The researchers on multi-criteria decision making will find the methodological enhancement proposed in terms of graphically deriving the transitive dominance to be useful in other applications as well.

Relationship of Manufacturing Flexibility with Organizational Strategy

“…Manufacturing flexibility is defined as the ability of the firm to manage production resources and uncertainty, cost-effectively to meet customer requests (Behrbohm 1985;Gerwin 1993;Watts et al 1993;Benjaafar and Ramakrishnan 1996;Tsourveloudis and Phillis 1998;Kathuria and Partovi 1999;Koste and Malhotra 1999;D'Souza and Williams 2000). A lot of researchers captured the multi-dimensional nature of manufacturing flexibility through different dimensions categorizing them into three major groups, namely inbound, in-house and outbound (Singh and Acharya 2013;Sushil 2018). Inbound flexibility addresses the unstable nature of customers for the procurement of raw materials or components from multiple sources for the manufacture of the product.…”

Flexibility in service operations: review, synthesis and research agenda

“…Although, several models have been proposed (e.g. Koste et al , 2004; Tachizawa, 2005; Cousens et al , 2009; Combe et al , 2012; Sushil, 2018) that attempts to clarify various issues as well as highlight the key aspects of flexibility. Regardless of recent attempts to review flexibility (Mishra et al , 2014; Yu et al , 2015), the literature does not contain a scientific and systematic approach to assess flexibility research.…”

Assessment of Shopping Mall Customers’ Experience through Criteria of Attractiveness in Tier-II and Tier-III Cities of India: An Exploratory Study

“…Similarly, Singh et al (2017) developed a model for green supply chain management which when implemented can change the current practices of fertilizer industry. It has found wide applicability in processing and structuring details related to any issue or activity such as career planning, process re-engineering, operations problem, strategic planning, product design, process design, complex technical problems, human resources, financial decision making, electronic commerce, healthcare, lean manufacturing, cloud computing adoption and competitive analysis (Faisal et al, 2006;Sahney et al, 2010;Attri et al, 2017;Sushil, 2018;Khaba and Bhar, 2018;Raut et al, 2018;Chaple et al, 2018;Ajmera and Jain, 2019). In retailing context, Venkatesh et al, (2015) used ISM in identifying supply chain risk variables in Indian apparel retail chain.…”