Satyendra Kumar Sharma

Modelling supply chain agility enablers using ISM

Purpose – The purpose of this paper is to present an approach to effective supply chain management by understanding the dynamics between various enablers of agile supply chain. Today’s business environment is characterized as a highly competitive, dynamic and volatile market. Agile supply chain is seen as the winning strategy to be adopted by manufacturers bracing themselves for dramatic performance enhancements to become national and international leaders. Design/methodology/approach – Using interpretive structural modeling the research presents a hierarchy-based model and the mutual relationships among the enablers of agile supply chain. Findings – The research shows that there exists a group of enablers having a high driving power and low dependence requiring maximum attention and of strategic importance, whereas another group consists of those variables which have high dependence and are the resultant actions. Practical implications – This classification provides a useful tool to supply chain managers...

Optimal selection of third-party logistics service providers using quality function deployment and Taguchi loss function

Purpose – Selection of logistics service provider (LSP) (also known as Third-party logistics (3PL) is a critical decision, because logistics affects top and bottom line as well. Companies consider logistics as a cost driver and at the time of LSP selection decision, many important decision criteria’s are left out. 3PL selection is multi-criteria decision-making process. The purpose of this paper is to develop an integrated approach, combining quality function deployment (QFD), and Taguchi loss function (TLF) to select optimal 3PL. Design/methodology/approach – Multiple criteria are derived from the company requirements using house of quality. The 3PL service attributes are developed using QFD and the relative importance of the attributes are assessed. TLFs are used to measure performance of each 3PL on each decision variable. Composite weighted loss scores are used to rank 3PLs. Findings – QFD is a better tool which connects attributes used in a decision problem to decision maker’s requirements. In total,...

Supply chain risk management dimensions in Indian automobile industry

Purpose – Globalization and outsourcing have rendered Indian automotive companies more vulnerable to supply chain (SC) risks. Consequently, companies adopt different supply chain risk management (SCRM) strategies to mitigate SC risks. The purpose of this paper is to explore SCRM strategies in Indian automobile industry and to classify automobile firms based on SCRM dimensions. Design/methodology/approach – A survey instrument on SCRM dimensions was designed and data were collected from 79 automobile firms. Principle component analysis (PCA) was performed on the collected data to derive the factors underlying SCRM dimensions. Further, cluster analysis using extracted factors as a clustering variate was performed to identify strategic groups from the given set of firms. Findings – PCA derived seven factors, namely: avoidance, supplier development, flexibility, risk pooling, redundancy, integration and control strategies. The surveyed firms were classified into two clusters as low and high SCRM level. Resear...

Identification and assessment of supply chain risk: development of AHP model for supply chain risk prioritisation

In modern times, competition has shifted from companies to supply chains and risk management has become one of the greatest challenge for supply chain managers. Risks affect supply chain performance hence supply chain risk assessment needs more attention. For this reason, this paper presents a general risks taxonomy and it gathers together, specifically the risks affecting the performance of an automotive supply chain. Further, the authors use analytic hierarchy process (AHP) methodology to analyse the risk factors. It is hoped, that this analysis will help managers, vendors, consultants and auditors to manage supply chain risks better. All risks that a supply chain might face have been identified, classified and ranked based on their risk exposure on supply chain. Results suggest that the most critical risks originate from supply side of the chain. The most important risks in automotive supply chain turn out to be volatile demand, financial failure of suppliers, supplier’s quality problems and failure to generate cost reduction.

An empirical exploration of supply chain design factors and their influence on supply chain performance

Supply chain management has become a competitive tool for companies to increase their profitability and supply chain performance is getting the attention of business executives. They have started to focus on various factors, (that are) responsible for supply chain performance. We present an extant literature review on various factors that enable supply chain performance. Further, we conducted a survey in the Indian automobile industry and have attempted to test empirically the relationship between various supply chain design factors and supply chain performance. Factors such as aligning incentives, integration, adaptability and contingency planning were found to be most important factors. However, similar studies need be conducted in other industries to generalise the findings of our survey.

Modeling information risk in supply chain using Bayesian networks

Purpose – Information sharing enhances the supply chain profitability significantly, but it may result in adverse impacts also (e.g. leakages of secret information to competitors, sharing of wrong information that result into losses). So, it is important to understand the various risk factors that lead to distortion in information sharing and results in negative consequences. Information risk identification and assessment in supply chain would help in choosing right mitigation strategies. The purpose of this paper is to identify various information risks that could impact a supply chain, and develop a conceptual framework to quantify them. Design/methodology/approach – Bayesian belief network (BBN) modeling will be used to provide a framework for information risk analysis in a supply chain. Bayesian methodology provides the reasoning in causal relationship among various risk factors and incorporates both objective and subjective data. Findings – This paper presents a causal relationship among various info...

An empirical investigation of the contribution of supply chain design characteristics on supply chain risks in Indian automobile industry

The importance of supply chain risk management is attracting the attention of academicians and business managers globally. As companies experience globalisation and cut throat competition, companies are forced to adopt measures to contain risk due to their supply chain design characteristics. The purpose of this paper is to identify supply chain design characteristics and investigate their relationship with overall supply chain risk. This research presents the empirical investigation of supply chain risk drivers. Analysis of responses from 102 executives from Indian automobile industry, give an insight into the relationship between key supply chain risk drivers viz. (supply chain complexity, focus on efficiency, dependence on few members and node criticality), and supply chain risks.

Developing a Bayesian belief network model for prediction of R&D project success

The project success is critical to the business performance in the era of fierce competition and globalization. The basis for project success lies in the capabilities of managing risks effectively. Innovation has always been considerably risky; however, managing Research and Development (R&D) project risks has become even more important given today’s tight schedules and limited resources. Risk management has to be an integral part of the development process. The purpose of this research is to develop a model to assess and estimate the risk exposure of an R&D project. A risk quantification model based on the Bayesian belief network is proposed, which is effective in capturing the interaction between various risk factors. The aim of this model is to empower the project managers to predict the failure risk probability of R&D projects.

Path Analysis Model for Supply Chain Risk Management

The purpose of this paper is to develop a model to understand the relationship of supply chain risk sources, risk drivers, and risk mitigation strategies to the overall risk exposure of the firm and to validate the model empirically. An attempt has been made to determine the major contributors of supply chain risk as viewed by automotive professionals in todays competitive market. This study empirically validates the effects of the three critical constructs on overall supply chain risk exposure. The limitations of this study can be seen in the use of perceptual data from single informants and the focus on automotive firms in a single country. The detailed operationalization of the constructs sheds further light on the major risk sources, drivers, and mitigation strategies in supply chain networks. Clear evidence of proactive strategies in mitigating risks provides managers with a business case to invest in such initiatives.

Risk Mitigation in Automotive Supply Chain: An Empirical Exploration of Enablers to Implement Supply Chain Risk Management

Supply chain (SC) risk management (SCRM) is a high-level concern for SC professionals. Supply chain risk management implementation is a difficult task because it requires involvement of various firms across the SC. For effective SCRM implementation, managers need to know the enabling factors and their relative importance. In this research, an empirical study on SC risk mitigation enablers was carried out in Indian automotive industry to examine the relationship between SCRM enablers and SCRM implementation. This relationship was tested using discriminant analysis. The research shows that the most important enabler is information visibility and it is followed by incentives alignment. Contingency planning is the third-most important enabler and last is risk management governance (RMG). Success of the SCRM implementation in terms of its efficiency and effectiveness can be assured by following the sequence of SCRM enablers suggested in this research.