Amol Singh

Sustainable green supply chain management: trends and current practices

Purpose The purpose of this paper is to give an up-to-date and structured insight into the literature published during the past decade on sustainable green supply chain management. It also suggests trends for future research based on the research issues identified through systematic and comprehensive analysis of previous studies in the area of green and sustainable supply chain management. Design/methodology/approach A state-of-the-art literature review is carried out by systematically collecting the existing literature over a period of 10 years (2005-2014) and categorizing it on the basis of attributes such as stages in supply chain, methodology and the industries/sectors under consideration. The classification of literature is also done according to the geographic region and year of publication. Findings There has been an increased interest among researchers and practitioners in the area of sustainable green supply chain management in the past decade. A need for achieving sustainability through adoption of greener practices has been universally felt, owing to an increasing environmental and ecological complexity. The review reveals that there exists a need to address behavioural issues like human resource management and supply chain partner relationship management. Moreover, reverse logistics, closed-loop supply chain management and waste management are areas that need special focus to achieve environmental sustainability. Research limitations/implications The current review focuses on research trends in the past 10 years only. Moreover, papers from only good quality, peer-reviewed journals are considered in the study. Originality/value Most of the previous reviews have either focused on specific issues related to sustainable supply chains only or green supply chains. The present study collectively takes into consideration papers both from green supply chain management as well as from sustainable supply chain literature that have a prime focus on environmental sustainability.

An interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL) method approach for the analysis of barriers of waste recycling in India

ABSTRACT Increasing amount of wastes is posing great difficulties for all countries across the world. The problem of waste management is more severe in developing countries such as India where the rates of economic growth and urbanization are increasing at a fast pace. The governments in these countries are often constrained by limited technical and financial capabilities, which prevent them from effectively addressing these problems. There is a limited participation from the private players too in terms of setting up of waste recycling units. The present study aims at identifying various barriers that challenge the establishment of these units, specific to India. Further, it attempts to identify the most influential barriers by utilizing multicriterion decision-making tools of interpretive structural modeling (ISM) and decision-making trail and evaluation laboratory (DEMATEL). The findings of the study suggest that the lack of funds, input material, and subsidy are the most influential barriers that are needed to be addressed for the development of waste recycling infrastructure in India. Implications: This work has been carried out to address the problem of proper waste management in India. To deal with this problem, the method of waste recycling has been felt appropriate by the government of various countries, including India. Therefore, the barriers that play vital role in waste recycling for private players have been identified and their importance has been established with the help of ISM and DEMATEL methods. Doing so will assist the government to take appropriate steps for the betterment of waste recycling infrastructure in India and enhance waste management.

Healthcare waste management: a state-of-the-art literature review

Enormous amount of waste generation is a critical issue across the world. This issue becomes more vital when various types of hazardous waste gets mixed up with general waste. One such hazardous waste is healthcare waste; this waste is generated in hospitals during different healthcare activities such as pathological diagnostic, surgery, etc. Therefore, to take an account on the issue of healthcare waste management the review of literature has been carried out on the basis of the classification given in Figure 1. This review article provides numerous future research directions including the requirement of more in-depth application of operations management tools and techniques. Additionally, the un-addressed issues related to a healthcare waste management i.e., inventory management, warehousing, bins allocation, routing and transportation, also needs attention for an effective management of healthcare waste.

An ARIMA model for the forecasting of healthcare waste generation in the Garhwal region of Uttarakhand, India

This study has been carried out to analyse and forecast the quantities of healthcare waste generated from the hospitals of Garhwal region of Uttarakhand, India. In this study, a suitable autoregressive integrated moving average (ARIMA) model has been developed, on the basis of different statistical parameters, for the forecasting of healthcare waste. The analysis of results on the basis of the statistical parameters such as adjusted R-square value, mean square error and mean absolute percentage error; the AR(1)MA(1) model has been found as the best ARIMA model for the forecasting of healthcare waste generation. The daily data of healthcare waste generation has been used to develop the ARIMA model in this study. The ARIMA model developed in this study would help the waste disposal firm to plan its waste collection and disposal strategy-related decisions in future.

Modelling the drivers of healthcare waste management in India: a policy perspective

The purpose of this paper is to explore the drivers of healthcare waste management from literature review and field survey and model these drivers for understanding the inter-relationships among the drivers to enhance healthcare waste management in the Indian context.,In view of the need of the study, the interpretive structural modelling (ISM) method has been applied to model the drivers. The ISM method helps in depicting the relationships among the drivers and filtration of drivers on the basis of their driving and dependence power.,The findings of the study reveal that the type of a healthcare facility and its management structure, size of a healthcare facility, human resource management of a healthcare facility, healthcare facility’s management monitoring and control, and the effective re-enforcement of government regulation and policy implementation in a healthcare facility play a vital role in the enhancement of HCWM.,The application of the findings of this study would enhance the hospital’s waste management by ultimately leading to a good ambience and satisfied patients and personnels. Additionally, the study would aid in the policy formulation by government and decision making of medical facilities, thereby strengthening HCWM scenario in the country.,The drivers filtered in this study would be useful for ranking the hospitals’ healthcare waste management in a region/country. This ranking may play a vital role in earmarking the hospitals which are managing their healthcare waste according to the guidelines of Central Pollution Control Board (CPCB) and Ministry of Environment and Forest (MoEF) of a country. With the help of this study, the problem of inadequate human resource can be effectively addressed for CPCB and MoEF, in India.,Healthcare waste management is a vital issue which needs attention from the management perspective in India. Therefore, an interpretive structural model, i.e. ISM digraph, has been developed which would help in the filtration of drivers and attaining the better healthcare waste management in an economically and timely manner.

Performance modelling of a flexible job shop by simulation and rerouting

The present research work focuses on the simulation modelling of a flexible job shop in order to improve its performance. The performance enhancement of a flexible job shop is carried out by reducing the effect of uncertainties with routing flexibility. Hence, a rerouting methodology has been proposed and it is used in the modelling of a flexible manufacturing job shop. The effectiveness of the rerouting methodology has been analysed by comparing it with other existing rerouting approaches such as all rerouting, queue rerouting, arrival rerouting, and one benchmarking approach, i.e., no rerouting. Mean flow time has been considered as a performance measure to evaluate the methodologies performance. These rerouting approaches are based on rerouting the jobs to their alternative machines when their primary machine fails. Further, simulation studies using ProModel® simulation software have been carried out at different breakdown levels, mean time to repair levels, and utilisation level. Simulation results indicate that the proposed rerouting methodology approach is better than other existing rerouting approaches as it improves 59.28%, 58.62%, 52.18%, and 29.79% of mean flow time compared with no rerouting, queue rerouting, arrival rerouting, and all rerouting approaches respectively.