The five papers published in this issue together offer theoretical and practical insights that hold immense value to the practice and research in Supply Chain Management (SCM).

In the first paper, “Analyzing the Product Substitution Approach in a Two-Stage Supply Chain”, by Srikanta Routroy and C V Sunil Kumar, a simulation model is developed for a two-stage supply chain for a multi-product configuration environment to study the impact of product substitution on supply chain performance along different dimensions and to determine the suitability of product substitution approach in a specific supply chain environment. Regression analysis is also carried out to establish the relationship between output parameters (i.e., total profit and product fill rate) and various input parameters.
The second paper, “Critical Success Factors for e-Gov Project: A Unified Model”, by Prabir Panda and G P Sahu, presents a detailed literature review to reveal that studies on the subject do not provide a synthesized framework for the identification and testing of Critical Success Factors (CSFs) in a particular cultural/environmental context. The authors aim to suggest a unified framework for identification of CSFs of any e-gov project, their empirical evaluation in various e-gov project stages, and subsequent classification into various project dimensions.

In the next paper, “Development of Supply Chain Tools Using Genetic Algorithm and Comparison with Particle Swarm Optimization and Simulated Annealing Optimization Algorithms”, by S Shakeel Ahamed, G Rangajanardhana and E L Nagesh, the optimized ordering quantity and reorder points are obtained with the aid of a proposed genetic algorithm. This proposed system considers the raw material-wise holding cost and shortage cost to find the minimized total cost. The ordering quantity and reorder points that minimize the cost function are found by using the demand rate as well as the associated solution demand matrix. Further, the robustness of the proposed technique is compared to that of the other familiar optimization algorithms such as particle swarm optimization and simulated annealing optimization techniques. The results prove that the proposed methodology is more efficient as compared to other optimization techniques.

The fourth paper, “Empowering Quality Management Systems Through Supply Chain Management Integration: A Survey of Select Hospitals in Chandigarh, Mohali and Panchkula”, by S K Chadha and Gagandeep, identifies whether supply chain management integration empowers quality management systems or not in the selected hospitals of Chandigarh, Mohali and Panchkula. The study also attempts to unblock the factors having a major impact on overall integration and overall quality management systems in the sample under study. Data collected through a structured questionnaire on a 5-point Likert scale is analyzed with the help of various statistical techniques like reliability analysis, factor analysis, and regression analysis. The results indicate that SCM integration catalyzes the quality management system in healthcare sector. With the help of these findings, the hospitals can reframe their strategies related to SCM to identify areas in which they can improve the quality of service for efficient patient care.

In the last paper, “Evaluation of Vendor Managed Inventory Elements in Manufacturing Sector Using ANOVA Technique”, by Viyat Varun Upadhyay, P C Tewari and Amit Gupta, the authors attempt to find various Vendor Managed Inventory (VMI) elements which are important to both the customer and the manufacturer (vendor) in the Indian context. The paper presents the relative importance and difficulties in the implementation of VMI elements in the manufacturing sector and the data is subjected to Analysis of Variance (ANOVA). The study also identifies the VMI elements which are most important and easy to implement in the manufacturing industries.

-- Sunil Bhardwaj
Consulting Editor