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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 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.

The first objective of this paper is to identify the critical success factors (CSFs) and their corresponding key performance indicators (KPIs) for supplier development (SD) in a manufacturing environment. The second objective is to develop a methodology to analyze and evaluate the performance for SD using CSFs and their KPIs over the time.

In all, 13 CSFs and their corresponding KPIs for SD are established through an extensive literature review, discussion held with managers/engineers in different Indian manufacturing companies and conducting brainstorming sessions. A methodology is proposed using analytic hierarchy process (AHP) and performance value analysis to assess and evaluate the performance of SD over the time.

From an extensive analysis of the results, under the given circumstances, the growth of SD performance is positive at different progressive points along the time horizon.

This study has not been statistically validated in manufacturing supply chain for complete acceptability.

This study provides insights into the performance evaluation of SD using CSFs and their corresponding KPIs. The managers should capture their manufacturing environment which can reflect their own priority considerations to establish the impact of each KPI on its corresponding CSF.

Although many issues related to SD have been widely researched individually, few studies have been reported with a model to quantify, monitor, analyze, and evaluate the growth of SD performance in manufacturing environment in Indian context. The proposed model has the ability to capture the performance along KPIs and CSFs to draw fruitful conclusions regarding the success of the SD programme.

The purpose of this paper is to identify and develop the structural relationship among the key drivers to control and enhance the supply management (SM) performance in Indian manufacturing environment.

The drivers (i.e. sourcing alternatives and supplier selection, supplier development (SD), contract management (CM) and risk management (RM)) of SM were identified and SM integration model was proposed through literature review and in consultation with industry experts. The proposed model was validated by capturing experts’ view in Indian manufacturing environment. The strength of relationships between these drivers and on SM performance was also established using structural equation modeling.

CM has positive direct effect on SM performance and two drivers (i.e. sourcing alternatives and supplier selection, and SD) have positive indirect effect mediated by CM. Whereas, RM has direct and indirect (mediated by CM) positive effect on SM performance in Indian manufacturing environment.

This model can be validated for manufacturing industries in other countries.

This model provides a comprehensive relationship among four drivers of SM and shows the direction for designing and implementing appropriate policies in order to enhance the SM performance in Indian manufacturing environment.

Although many issues related to SM have been widely researched, but no literature has been reported related to SM integration model consisting of its drivers in general and in Indian manufacturing environment in specific. The key drivers of SM were identified and their relative importance was analyzed in Indian manufacturing environment.

The aim of this paper is to propose a benchmarking model of supplier development (SD) for an Indian gear manufacturing company for its successful adoption and improvement in a continuous basis.

Thirteen SD critical success factors (CSFs) are identified and classified into four categories through extensive literature review and discussion held with managers/senior engineers in different Indian manufacturing companies. The four categories are primary CSFs related to supplier, secondary CSFs related to supplier, CSFs related to manufacturer and CSFs related to both manufacturer and supplier. The interpretative structural modeling (ISM) approach is applied to the Indian gear manufacturing company for developing and analyzing structural framework of CSFs to propose a benchmarking model for SD.

It is concluded that SD adoption should be carried out in four phases sequentially for the Indian gear manufacturing company. The first, second, third and fourth phase should sequentially focus on primary CSFs related to supplier; secondary CSFs related to supplier; CSFs related to manufacturer; and CSFs related to both manufacturer and supplier, respectively. The proposed benchmarking model has four phases (i.e. plan, analyze, implement and measure) and bifurcated into 12 steps to enhance the performance of CSFs.

This paper provides a useful benchmarking model for successful adoption of SD in manufacturing organizations.

This is one of the few studies to develop the relationship of CSFs for SD in general and its application to an Indian gear manufacturing company in particular. A benchmarking model for SD is also proposed having five phases and 12 steps. The findings of the proposed structural framework and benchmarking model for the Indian gear manufacturing company are discussed in detail and will serve as a guideline for successful adoption of SD in manufacturing environment.

The purpose of this paper is to identify, analyze, assess and manage the risks issues involved in an Indian manufacturing supply chain. The paper also shows the direction to use the proposed comprehensive risk management framework in different manufacturing supply chain.

The various risks for an Indian manufacturing company are identified through brainstorming session held with managers and engineers. The risks are categorized (i.e. delivery performance; process capability; demand and supply fluctuation at supplier end; rework; and business practices) and the domain (i.e. supplier, manufacturer and customer) of each risk is also identified for further analysis. A Failure Mode and Effect Analysis is used to rank the impact of all the relevant risks associated with various risk categories and the action plans are suggested by proposing a risk treatment process.

The degree of impact of each relevant risk is determined and is used for deriving managerial insights. Through Pareto analysis, it is concluded that top 20 percent risk factors are coming from supplier and organization domain. It is interesting to note that no relevant risk related to customer domain is appearing in top 20 percent. It is also found that 54 percent risk is coming from supplier-related risk domain and 46 percent risk exists in the organization-related risk domain among top 20 percent risk.

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 more generalized impact of risks, its validity and their variation across the different manufacturing companies.

The simplicity and clarity of the proposed framework provides step-by-step approach for identifying, categorizing and managing risks involved in the supply chain. It also provides the guidelines for a manager to benchmark and update risk handling in a specific manufacturing environment with its own priority considerations.

Although many literatures are available related to supply chain risk management, the proposed approach provides a better practical generic platform to understand, manage, reduce and mitigate the risks involved along the manufacturing supply chain.

The purpose of this paper is to analyze the sourcing alternatives (i.e. supplier development (SD), supplier switching (SS) and in‐house production (IP)) in an Indian manufacturing supply chain environment.

A total of 14 attributes are identified through an extensive literature review and discussion held with managers/engineers of different Indian manufacturing companies for analyzing the sourcing alternatives. A systematic methodology is proposed and applied, comprising a fuzzy analytic hierarchy process (FAHP) for analyzing the sourcing alternatives followed by the application of classical analytic hierarchy process (AHP) for result verification.

From the results obtained from both AHP and FAHP, it is established that the SD is the most preferred alternative in comparison to other two alternatives (i.e. SS and IP) for the considered Indian manufacturing environment.

The same problem can be extended by incorporating the dynamic behavior of the attributes. The findings cannot be generalized for any other company as it is based on a single Indian manufacturing company.

The paper demonstrates a methodology to evaluate the sourcing alternatives considering judgment of multiple experts in a systematic way. It is believed that it will be quite useful for the supply chain manager to analyze sourcing alternatives by capturing his manufacturing environment into priority weights, which can reflect his priority considerations.

Although SD, SS and IP have been widely researched individually, no study has been reported in the literature to evaluate and rank these three alternatives in any specific Indian manufacturing environment.

The purpose of this paper is to identify and evaluate the critical success factors (CSFs) responsible for supplier development (SD) in a manufacturing supply chain environment.

In total, 13 CSFs for SD are identified (i.e. long‐term strategic goal; top management commitment; incentives; supplier's supplier condition; proximity to manufacturing base; supplier certification; innovation capability; information sharing; environmental readiness; external environment; project completion experience; supplier status and direct involvement) through extensive literature review and discussion held with managers/engineers in different Indian manufacturing companies. A fuzzy analytic hierarchy process (FAHP) is proposed and developed to evaluate the degree of impact of each CSF on SD.

The degree of impact for each CSF on SD is established for an Indian company. The results are discussed in detail with managerial implications. The long‐term strategic goal is found to be the most significant CSF for successful SD implementation.

This study has not been statistically validated in a manufacturing supply chain environment for complete acceptability.

The simplicity and clarity of the proposed approach enhances its acceptability for evaluating CSFs in manufacturing supply chain environment. It also provides the direction for optimally allocating the efforts and resources for successful implementation of SD in short duration.

Although both CSFs and SD have been widely researched, but no study has been reported in the literature to prioritize and rank the CSFs of SD in an Indian manufacturing environment. The paper contributes to research in the supply chain management area in general and SD in particular for manufacturing environment. The proposed approach has the ability to capture the judgment of multiple experts to prioritize and rank CSFs for SD.