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A literature review revealed that government of various developing economies have put an effort on health-care supply chain through the executing critical factors (CFs) directly. Although they have attained some significant benefits in this tactic, but it was not up to satisfactory level. One of the reasons can be attributed to the fact that government/policy makers are not quantifying the impact of CFs on health-care supply chain. This paper aims to propose a methodology to quantify and estimate the impact of CFs on government-supported health-care supply chain (GHSC).

The Graph Theoretic Approach is proposed for estimating the impact and utility of CFs on an Indian GHSC. This study is also extended to scenario analysis for comparing results with different performance situation.

The results obtained from this study show that performance of Indian GHSC is satisfactory, but performance gaps exist which need to be reduced. In this research work, 12 CFs are identified under two significant categories (SCs), i.e. enablers and barriers and the intensity of enablers and barriers have been calculated to show the impact or influence of CFs on GHSC. The value of intensity shows that the role or impact of enabler category (i.e. performance measurement, employee recognition and reward, technology adoption, training cell, inbuilt analytical tool for IT system) is higher on Indian GHSC in comparison to barriers category to enhance the performance of GHSC.

The obtained numerical results are completely in specific to the Indian perspective only; hence, they cannot be generalized for other countries. Simultaneously, this study is related to government supported health-care system; hence, the selection of expert panel was crucial due to the unavailability of doctors and other stakeholders of government system.

The proposed approach is aimed at providing a procedure for evaluating the impact of CFs on HSC in general and GHSC in specific. This study is an attempt to assist government and top management of GHSC to assess the impact of CFs on GHSC and accordingly define its course of actions.

Although various issues related to the CFs have been broadly identified and analyzed, no dedicated study has been reported in the field for quantification of impacts of CFs. Furthermore, this proposed model has an ability to recognize the specific contribution of each CF and overall contribution.

Dealers positioned at the downstream of the supply chains are those who can directly influence demand scenario for the manufacturer. However, manufacturer has to ensure that the influence is favorable by competitively fulfilling the anticipations of the dealers. In this regard, the purpose of this paper is focused on developing sustainable strategic relationships between manufacturer and dealer.

In this paper, the basic requirements of the dealers expected to be fulfilled by a manufacturer are analyzed by applying fuzzy Analytic Hierarchy Process and fuzzy Quality Function Deployment. The said approach is implemented in a case situation of a paint manufacturing company in India, and the results are analyzed to provide directions for the company to strategically align manufacturer–dealer relationships.

It was found that the case company has to focus mainly on promotions and advertisements, painters meet, and recognition offered to the dealers. Although pricing was also considered as one of the prominent aspects yet through competitive assessment the case company was found to be better off compared to its competitors.

As the results obtained in the current study are specific to a manufacturing environment, they cannot be generalized for all the companies. However, similar approach can be adopted for analyzing the customer requirements in order to achieve dealers’ attractiveness and satisfaction.

The application of proposed approach assists a manufacturer to pursue right strategy to practice for achieving dealer attractiveness and satisfaction. This will definitely help the supply chain managers to have the right requirements of the dealers’ are fulfilled on priority.

The purpose of this paper is to develop a set of key performance indicators (KPIs) for agile manufacturing (AM) and to propose a methodology for its performance evaluation.

The proposed methodology was developed using fuzzy analytic hierarchy process (FAHP) and performance value analysis (PVA) to evaluate and analyze the AM performance. The FAHP is applied to determine the importance of KPIs, and PVA is used to evaluate AM performance.

The proposed methodology is applied to an Indian auto component manufacturer, and it is observed that there is an improvement of performance along the timeline.

The proposed approach is generic in nature and can be applied to different agile business environments for performance evaluation.

This study provides insights into the AM performance evaluation. The managers can establish the impact of each significant area (SA) on AM and each KPI on its corresponding SA by capturing their manufacturing environments.

Although many issues related to AM have been widely researched, only a few studies have been carried out to quantify, analyze and evaluate the AM performance in the Indian manufacturing environment. The proposed model has the ability to capture the performance of AM along the KPIs to draw fruitful conclusions.

The purpose of this paper is to quantify, evaluate and compare the implementation performance of a supplier development (SD) program using graph theoretic approach (GTA).

Broadly 13 critical success factors (CSFs) were identified and they were classified into four significant categories (SCs). Featuring these SCs and CSFs under each SC, GTA was proposed for evaluating the implementation performance of SD programs. The analysis was further extended to evaluate the performance of a SD program along the timeline to capture the other influences (if any), eventually compare the results with different performance situations and accordingly set the future targets.

In order to demonstrate the utility of the proposed approach it was applied to an Indian manufacturing company. The results obtained shown that there has been a significant growth achieved in the implementation performance of a SD program over a period of three years (i.e. 12 quarters) along the chosen SCs and CSFs under each SC. It was also found that still there was a performance gap and scope for improvement in the SD program of the case company.

The proposed approach is aimed at providing a procedure for evaluating the implementation performance of a SD program. This study is an attempt to assist a manufacturer to assess its SD program and accordingly define its course of actions.

Although many issues related to SD have been widely recognized and studied, there are no specific studies available in the literature to assess the implementation performance of SD programs along the timeline. The proposed model has the ability to capture the performance and interdependencies of SCs, CSFs under each SC and also to quantify the implementation performance of a SD program along the timeline.

Drug warehouses (DWs) play a crucial role in drug distribution of government-supported healthcare supply chain as it controls both the cost and responsiveness of the logistics activities. The current study proposes a methodology using data envelopment analysis (DEA) to estimate the performance along different dimensions and was applied to 30 government-supported DWs.

This study employs DEA to evaluate the performance and relative technical efficiency of DWs. In this research, four inputs and six outputs are identified based on intensive literature review and discussion with all stakeholders of DWs. The inputs are warehouse storage capacity, temperature-controlled storage capacity, number of skilled employees and operational cost, while the outputs are fill rate, number of generic drugs, volume of drugs, consumption points, inventory turns ratio and time efficiency.

Results show that 30% DWs operate at the most productive scale size with 100% efficiency level while 47% DWs have a significant possibility for further enhancement in productive efficiency and 23% DWs should diminish their operational size to increase their productivity level. It was also found that achieving 100% operational productivity along warehouse space capacity needs significant effort, whereas other three inputs, namely temperature-controlled capacity, number of skilled employees and operational cost, require comparatively less effort. Similarly, it was observed that the performance along the fill rate and time efficiency is satisfactory, whereas the performance along other fours output variables (i.e. number of generic drugs, volume of drugs, consumption points and inventory turns ratio) needs to be improved.

The findings offer insights on the inputs and outputs that significantly contribute to efficiencies so that inefficient DWs can focus on these factors.

Although many issues related to DEA have been widely researched and reported, but no literature has been found for analysis of DWs in general and government-supported DWs specifically to find out efficiencies for supply chain performance improvement.

The purpose of this paper is to identify, analyze and classify (i.e. driving and dependence power) the government-supported health-care supply chain enablers (GHSCEs) in rural areas of India for enhancing availability and minimizing wastage of generic medicines.

A methodology is proposed using interpretive structural modeling (ISM) – fuzzy matriced impacts croises multiplication appliqueeaun classement (Fuzzy MICMAC) analysis to analyze the GHSCEs on the basis of inputs collected from various stakeholders about their driving and dependence power.

The performance measurement system, employee recognition and reward, technology adoption, training cell and inbuilt analytical tool for IT system were found to be the appropriate GHSCEs where efforts and resources should be put for enhancing availability and minimizing wastage.

The proposed approach provides a platform for the both researchers and academicians to understand the GHSCEs and their relationships. It also provides the direction to the government for optimally allocating the efforts and resources to enhance the current performance level of generic drug distribution.

Although many issues related to health-care supply chain have been widely researched and reported, no literature has been found for analysis of GHSCEs to choose the appropriate set of GHSCEs for supply chain performance improvement in general and developing country like India in specific.

The requirement of high-quality government-supported healthcare services has necessitated the significance of recognizing new management practices to enhance patient satisfaction. Hence, the purpose of this study is to address the patient's enhanced custom needs through the implementation of supply chain value stream mapping (SCVSM) in government-supported drug distribution system (DDS) for enhanced patient's satisfaction.

This study elucidates the role of one popular emerging management technique (i.e. SCVSM) in the healthcare sector by an investigative case study. The DDS in Rajasthan (India) was selected for this study. The data for this analysis were gathered in three ways (i.e. direct observation, documentary analysis and semi-structured interviews).

The outcome of this current study reveals that it is possible to apply the tool (SCVSM) to investigate the wastes in DDS to deliver the medicines at right time, right quantity and right quality. The application of SCVSM concluded that the various Kaizens (areas needed to improve) in lead time; transportation and routing should be adopted. The study further implemented kaizen on the current SCVSM and developed future SCVSM.

Although various stages and functions exist in the healthcare supply chain, the current study is focused on the distribution system of drugs. The proposed approach provides a platform for both researchers and academicians to understand the existing DDS and to implement the SCVSM approach in the healthcare environment. The results show that the proposed SCVSM model is able to identify some operational bottlenecks and wastes which interfere in DDS.

It was observed that limited literature related to lean implementation on DDS and implementation of SCVSM on the healthcare environment in general and government-supported or public in specific are available. The current study on the application of SCVSM in DDS is unique in nature and will definitely add value to the existing literature of the application of value stream mapping (VSM) on the healthcare supply chain management field.

The purpose of this paper is to identify, analyze and orient the enablers of Six Sigma to enhance supplier capability for an Indian manufacturing supply chain (SC).

In total, nine enablers of Six Sigma were identified through an extensive literature review and discussion held with managers/senior managers in different Indian manufacturing companies. The interpretative structural modeling (ISM) approach is applied to the Indian auto ancillary company for developing and analyzing the structural framework of enablers to enhance the supplier capability.

The enablers such as top management commitment and leadership, supply chain management, standardization, training and education, human resource management and project selection and execution methodology of Six Sigma related to supplier capability have emerged as the prominent enablers, which are driving force in the system for the Indian manufacturing SC.

This study is restricted to only one Indian manufacturing company. Therefore, the outcomes of the study should not be generalized. Further studies may be carried out for several Indian manufacturing industries to get a more comprehensive implementation approach, their validity and their variation across the different industries.

The simplicity and clarity of the proposed structural framework of Six Sigma helps in the identification and orientation of enablers for the successful implementation of Six Sigma in the SC. The proposed structural framework can be applied to different manufacturing SCs by allowing managers to structure the enablers considering their unique implementation constraints, which can reflect their priority considerations.

The study goes beyond the conceptual discussion of supplier capability issues. The supplier capability cannot be seen as a standalone approach irrespective of the constraints from the supplier domain as it is in synchronization with the entire SC performance. The enablers and their orientation with respect to the SC are providing a unique contribution toward supplier management planning. The outcomes from the proposed structural framework are used for developing action plans for organization “A” or other organizations to build suitable supplier capability in the SC.

The purpose of this paper is to evaluate the agility performance level of manufacturing supply chains using Taguchi loss functions (TLFs) and design of experiment (DoE).

The proposed methodology is used for capturing the various agility losses using appropriate TLFs and the aggregated agility loss is calculated at different situations using DoE. The aggregated agility loss is analysed for comparing manufacturing supply chain agility performance.

The proposed methodology was applied to three Indian auto component supply chains, i.e. X, Y and Z. In total, 27 experiments were carried out using DoE and obtained results show that agility performance level is the highest for X followed by Z, whereas agility performance level is the least for Y.

The proposed methodology is generic in nature and can be applied to a specific environment for comparing performance of different supply chains. The user has to identify the relevant agility enablers and capture the appropriate TLFs for the specific environment in which agility performance level has to be calculated and compared.

The proposed methodology provides an effective approach for evaluating agility performance. It can be used by the supply chain manger to assess the supply chain agility performance level of own company with its competitors. These comparisons will help the manufacturing company to find the areas where it should focus.

Many studies and researches related to implementation and evaluation of agile manufacturing are reported in the literature but very few studies are available for evaluating the supply chain agility performance. This study will definitely provide a guideline for measuring and comparing manufacturing supply chain agility performance in general and Indian automotive supply chain in specific.

The purpose of the paper is to identify, analyze and select the enablers for vertical integration of Aloe vera supply chain (AVSC) so that rural employability will be enhanced in the context of Rajasthan, India.

Interpretive structural modeling (ISM) was proposed to develop a structural model to identify the right enablers for enhancing the rural employability and business prospects. Also, fuzzy-matrix cross-reference multiplication applied to classification (F-MICMAC) was applied to segregate the enablers into four clusters on the basis of their driving and dependence power. Finally, the significant enablers were selected.

Out of identified 13 enablers, three enablers (i.e. institute for training and research, transportation infrastructure and government incentives for value addition) were appearing at the bottom of the ISM structural model and also in the driving quadrant of driver-dependent diagram. Therefore, they are the significant enablers for vertical integration of AVSC to enhance the rural employability in the context of Rajasthan, India.

The interactions among enablers are not statistically validated. However, the empirical analysis and total interpretive structural modeling may be used for this purpose.

The outcomes of the study will provide the guidelines for implementation of vertical integration at the village level to enhance rural employability in the context of Rajasthan, India in specific.

Although a few studies have been reported in the literature related to value-addition process (vertical integration), but the modeling of enablers to segregate and identify the appropriate enablers for vertical integration of AVSC for enhancing employability at the rural areas is unique.