The concept of flexibility in the field of operations management has created interest amongst researchers and supply chain practitioners. The work of Browne et al. (1984) and Sethi and Sethi (1990) were some of the earliest works that motivated many researchers to further contribute high research output in this area. Increasing manufacturing flexibility is a key strategy for efficiently improving market responsiveness because of fluctuations in demand and high uncertainty. Manufacturing flexibility triggers flexibility in process so that different products can be manufactured in the same plant or production facility at the same time (Jordan & Graves 1995). Manufacturing flexibility further necessitated flexibility in procurement systems to provide the firm the ability to respond quickly to demand changes, volume changes and to manage supply risks (Dubey & Ali 2014). The matter has become more complicated today where sustainability is a real challenge for business success. Globally, researchers and supply chain practitioners are looking for innovative practices to achieve sustainability and enhance supply chain performance. Various case studies are available on supply disruptions which impacted the entire supply chain network and resulted in huge financial losses. Bag and Anand (2015) have identified the leading barriers of sustainable supply chain network design and further extended the knowledge base. Supply chain practitioners are now searching for innovative methodologies to integrate flexibility in procurement processes and design the supply network for better risk management. This is a burning problem that procurement managers are facing and has been the motivating factor in conducting the present study. The purpose of the study is to provide a brief conceptual review of flexible procurement systems (FPSs). Further, the elements of FPSs are modelled using total interpretive structural modelling (TISM).
Concern related to FPSs in achieving business sustainability is growing from past few years. Collectively, these concerns involve a higher number of interaction factors, which further increase the complexity by decreasing the visibility of risks in supply chain network and so add to its vulnerability. To improve the situation, proactive planning and understanding the interplay of the elements are necessary for decision making.
The first research question attempts to understand what work has been carried out in the past on ‘flexible procurement system’. The second and third questions have been addressed using the TISM approach.
For literature review, scholarly works from databases such as Science Direct, Compendex, Ebsco, Emerald and Scopus have been used. There are lots of publications available in the area of flexible manufacturing systems, but very limited research studies are available which specifically address FPSs.
Keeping the research objectives in mind, the focus is on identifying elements or dimensions of FPSs. Here researcher based on literature review prepared a non-exhaustive list of elements of FPS which are presented in Table 1.
Flexibility can have important consequences for the organisation efficiency and long-term sustainability of an organisational system. It should be considered explicitly as a decision factor in designing supply chain network.
Purchasing flexibility is defined as ‘the ability to meet the changing needs of customers, changing the supply of products, including mix, volume, product variations and new product’ (Duclos, Vokurka & Lummus 2003:446–456).
Studies are mostly available related to risk management, which is very important for organisation sustainability. Shah (2008) focused on the determinants of supply-side risks. Later, Jung, Lim and Oh (2011) developed a supplier risk assessment model for buyers to estimate supplier risks. In another case study by Ganguly (2013), investigation was done to understand supply risk and the implications and measures for supply risk management. Also, there are studies available on managing purchasing risks. Lockamy and Mc Cormack (2010) presented Bayesian networks methodology for creating profiles of individual suppliers for analysing risks in supply networks to facilitate outsourcing decisions. Researchers found that flexibility is an important component in purchasing without which the purchasing system will collapse considering the present dynamic business environment. Chan, Bhagwat and Wadhwa (2009) presented a simulation study on suppliers’ flexibility level in relation to information system automation level of the supply chain and physical characteristics of the flexible suppliers. There are immense benefits of flexible purchasing system. Lawson et al. (2009) found that strategic purchasing is significantly and positively related to higher levels of socialisation and supplier process integration. Collaborative relationships will lead to develop green innovative products at an economical cost (Bag, in press).
Several researchers have also suggested developing flexibility in contract management. Li and Kouvelis (1999) illustrate that the contractual flexibility in sourcing arrangements, when carefully exercised, can effectively reduce the sourcing cost in environment of price uncertainty. Brockett, Golden and Panjer (1996) presented a general framework for purchase frequency modelling that enables flexible fitting and convenient competency.
From a review of literature, it is found that on-time delivery, strategic sourcing, environmental certification and management of transportation systems are main priorities in FPSs.
The TISM approach is used to develop the hierarchical relationship amongst the elements of FPS. TISM is a proven and popular methodology for understanding relationships amongst specific items that define a problem. TISM is useful to achieve the objective in the presence of a large number of directly and indirectly related elements and complex interactions amongst them, which may or may not be expressed in a proper manner. TISM is an innovative version of Warfield’s interpretive structural modelling (ISM) technique and is used to model and structure the FPSs for greater understanding of the interplay of these forces. Earlier, TISM had been used in the broad field of management science by several researchers (Jayalakshmi & Pramod 2015; Mangla, Kumar & Barua 2014; Nasim 2011; Prasad & Suri 2011; Sandbhor & Botre 2014; Singh & Sushil 2013). Here, the steps in TISM are followed as suggested by Sushil (2012). Experts’ opinions from industry and academia have been sought to identify the contextual relationships amongst each pair of elements and also the underlying reasoning behind each relationship. Developing TISM model for ‘n’ elements, an expert is supposed to define and provide reason for n*(n − 1) pairs of relationships.
The first step of the modelling is to identify and define the elements whose relationships are modelled. In context to the study, 10 elements related to procurement that play a key role in FPSs is identified from literature review and through semi-structured interviews (Table 2). These 10 elements have been further validated in consultation with 6 supply chain experts having more than 20 years of experience and who were professional members of Operations Research Society of India (ORSI) and Chartered Institute of Logistics and Transport (CILT).
To build the TISM model, it is vital to state the contextual relationship between different elements, which is given in Table 3. The inputs of six supply chain experts are solicited to capture the contextual relationship between the elements.
TISM is a superior technique over traditional ISM. ISM remains quite on how the relationship actually works. In TISM, clarifications from supply chain experts have been asked for the logic behind the expressed relationship. TISM brings more transparency and better understanding of problem links.
Here, the concept of Interpretive Matrix is applied to fully interpret each pair of comparison by explaining the interpretive query as mentioned in the previous step.
The paired comparison in the Interpretive Logic-Knowledge Base is translated in the form of a reachability matrix by making entry 1 in the i - j cell, if the corresponding entry in the knowledge base is ‘Y’, or else it should be entered as 0 for the corresponding entry ‘N’ in the Interpretive Logic-Knowledge Base. The matrix has also been checked for transitivity rule. A final reachability matrix, post-transitivity check is presented in Table 5. Also, for each new transitive link, the Interpretive Logic-Knowledge Base is also updated. The ‘No’ entry is to be changed to ‘Yes’, and in the interpretation column, ‘Transitive’ is entered.
The elements are arranged graphically in levels and the directed links are drawn as per the relationships shown in the reachability matrix. A diagraph with significant transitive links as per levels achieved in the previous step is presented in Figure 1.
The final digraph is converted into an interaction matrix (binary matrix) form depicting all the interactions by ‘1’ entry. The cells with 1 entry are interpreted by picking the relevant interpretation from the knowledge base in the form of interpretive matrix. An interaction and interpretive matrix for Figure 1 is presented in Table 8 (a and b). Finally, the diagraph (Figure 1) is translated into ISM by interpreting the node in box-bullet representation as shown in Figure 2.
The connective and interpretive information contained in the interpretive direct interaction matrix and diagraph is used to derive the TISM. The nodes in the diagraph are replaced by the interpretation of elements placed in boxes. The interpretation of the cells of interpretive direct interaction matrix is depicted by the side of the respective links in the structural model. The final TISM model is presented in Figure 3.
The 11 findings of TISM are discussed in the section for gaining deeper insights of FPSs and its link with supply chain sustainability.
Firstly, the TISM-based model evaluates the causality and illustrates elements with interpretation of relations and suggests that bottom-level elements are vital for sustainability in FPSs to avert risks.
Secondly, strategic sourcing is positively influencing supplier integration. Manufacturing organisations having a strong sourcing policy successfully integrate suppliers. This helps in greater level of flexibility and develops more innovative products successfully.
Thirdly, supplier integration positively influences supplier responsiveness. Those manufacturers who adopt supplier collaboration and integrate procurement with other functions generate higher level of supplier responsiveness.
Fourthly, skills of flexible procurement workforce positively influence supplier integration. Broad mix of technical, clear communication and managerial skills is essential for collaboration with green suppliers.
Next, it is found that supplier integration positively influences flexible transportation. Collaborative planning and sharing of information help to proactively plan and schedule vehicles to meet fluctuations in production demand. This helps in optimising fuel consumption and reduces carbon footprint.
It is also found that supplier integration positively influences eco-friendly packaging. Firms investing in supplier partnerships achieve better reduction in wastage. Joint planning helps in identifying raw material to be used for packing. This assists in the selection of non-hazardous chemicals usage for treating the packing material. This also enables cutting costs in the entire packaging process and builds sustainability.
The next finding highlights that supplier integration positively influences ISO 14001 certification. Collaborative planning and information sharing assist to identify the strengths and weakness of suppliers. This will enable to educate and train suppliers and for environmental certification. This is a flexible mode of moulding strategic suppliers and develops sustainability.
Another finding explains that supplier responsiveness positively influences customer satisfaction. Trust and collaborative efforts between buyers and suppliers improve delivery and product quality, which enhance customer satisfaction and are considered as a move towards sustainability.
It is also observed that flexible transport reduces operational cost and environmental costs. Flexible transport also enhances customer satisfaction. This leads to supply chain sustainability.
The second last finding explains eco-friendly packaging and reduction in environmental cost by careful selection of packing materials and chemicals. Eco-labelling, environmental improvement of packaging and recycling packaging material reduce waste and emissions and cut packaging costs. Eco-friendly packaging enhances company image and enhances customer satisfaction.
Lastly, it is found that ISO 14001/environmental certifications reduce environmental costs by greening suppliers and pressurises them to follow environmental norms. This helps in reducing wastage and developing alternate raw materials that are eco-friendly in nature. Environmental certifications of suppliers help in improving the image of buyer firms in the business environment and attract more customers.
The present study is based on two prolonged strategies. Firstly, literature review is done to identify the elements of FPSs. Secondly, TISM approach is used to identify the contextual interrelationships of a FPS. It is found that FPSs have a positive relationship with supply chain sustainability. The findings are really interesting and extend the existing knowledge base. The study will enable supply chain practitioners in building flexible procurement strategies for sustainable supply chain management. This will also enable business excellence in this high-risk uncertain supply network environment.
The present research has employed TISM methodology. Similar to other methodologies, TISM also suffers from certain limitations. The proposed TISM model is not statistically validated. To eradicate the limitation, the Structural Equation Modelling technique can be applied for statistical validation and is one of the future research directions. Further empirical surveys using a big sample size may also be conducted to compare the model.
The author wishes to thank all the reviewers for their helpful and valuable comments on the paper. The author is also thankful to Dr (Prof.) Rameshwar Dubey for his encouragement in developing the article.
The author declares that he has no financial or personal relationships which may have inappropriately influenced him in writing this article.
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