Search results

During pre-vaccine era, pharmaceutical supplies [self-care essentials (SCEs)] have been proved to be a major deflector, protector and safety guard against novel coronavirus disease (COVID-19). Hence, the objective of the study is to provide a comprehensive socio-technological decision-making framework based on multiple criteria for selecting the suppliers of pharmaceuticals, such as SCEs, by multi-brand enterprises (distributors) in the pandemic environment.

A hybrid methodology of Bayesian best worst method (BWM) and multi-attributive border approximation area comparison (MABAC) method has been applied for carrying out the study. Bayesian BWM has been applied for computing the importance of criteria identified for the selection of SCEs' suppliers during pandemic environment and MABAC method evaluated the suppliers of the SCEs.

In the study, the authors have identified eight criteria such as disinfection and sanitization of vehicles, social conscience of suppliers, brand (Technological recognition) of SCEs and logistics and distribution network, among others, which are critical to the selection of a supplier for the supply of SCEs. The application of the proposed hybrid model revealed that lead time and quality of SCEs are of utmost concern for pharmacies in a pandemic environment. Among the ten suppliers, results showed that Suppliers 2, 4 and 5 have been ranked first for supplying hand wash, hand sanitizer and face mask, respectively.

The proposed model has helped the multi-brand distributors of pharmaceuticals in selecting suppliers during the ongoing crisis of COVID-19. In addition to that, in future the outcomes of the study would be helpful for multi-brand distributors as well as pharmacies and hospitals in selecting the best suppliers. Policy makers will be able to make and revise the policies immediately with the help of the proposed decision-making framework.

The paper makes a novel contribution towards theory with the criteria identified for selecting best suppliers during the pandemic COVID-19. Additionally, the proposed hybrid model helps multi-brand distributors of pharmaceuticals in making decisions that lead to a huge social and economic success in pandemic time.

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.

The waste of invaluable agri-food produce is the concern of United Nations Organisation and all countries across the world. The purpose of this paper is to identify and model the drivers of agri-food waste management in India.

The interpretive structural modelling method is used to model the drivers in this study. This method helps in understanding the driver-dependent relationships among various drivers/criteria which are selected for studying.

The findings of the study vividly shows that the drivers such as disaster management planning, information dissemination, and training and awareness programs for farmers are most vital for tackling the issue.

This work would help the policy makers in developing the effective policies regarding the management of agri-food waste in a sustainable manner.

This work would be very helpful for deeply understanding the causes of occurring waste and carefully handling it scientifically with a managerial perspective. Hence, it has the potential to reduce the generation of waste and saving the food for society.

With the help of this study, the people, society, and underprivileged will be benefited directly. The savings in agri-food waste will not only help in controlling the prices of it but also its more availability would be beneficial for all in beating the hunger.

The identification of drivers for the sustainable management of agri-food is the novelty of this research.

Climate change and global warming pose a serious threat to the community as deglaciating environments trigger glacial lake outburst floods (GLOFs). The Sendai framework underpins the role of disaster risk reduction (DRR) for sustainable development, thereby calling for the development of GLOF hazard and risk assessment procedures. This study aims to delineate the enablers of GLOF risk and establish a contextual relationship between them.

The risk enablers are identified from the extant GLOF literature, and the experts from disaster management area are consulted to explore the underlying contextual relationship among them. An interpretive structural model is developed from the responses to analyze the contextual relationships among the risk enablers.

The interpretive structural modeling results manifest that seismic activity, temperature and precipitation events, and proximity are key drivers that trigger flash floods from the lakes and an effective assessment of these triggers may contribute significantly to GLOF risk mitigation.

The study models the complex relationship among the risk enablers for a glacial flood hazard that find commonality across all geographic contexts. The findings provide the practitioners of DRR useful insights into these factors and their subsequent impact on others, while conducting hazard assessment of glacial lakes that may contribute to the sustainable development of settlements lying downstream to glacial lakes.

The problem of evaluating potential suppliers has always been based on finding an optimal tradeoff between supplier’s performance consistently meeting firms’ needs and acceptable cost. The purpose of this paper is to propose a hybrid multi-criteria decision framework to quantify this qualitative judgment and reduce ambiguity in selection of suppliers in the era of Industry 4.0.

A hybrid intuitionistic fuzzy entropy weight-based multi-criteria decision model with TOPSIS is proposed. The authors make use of the intuitionistic fuzzy weighted approach operator for aggregating individual decision maker’s opinions regarding each alternative over every criterion. Additionally, the authors employ the concept of Shannon’s entropy to calculate the criteria weights.

Results obtained on the basis of the proposed hybrid methodology are analyzed against two more cases wherein the authors try to showcase the relevance of using IFS and entropy-based decision framework and find out the uniqueness of the proposed framework in supplier selection process.

The proposed model is apposite to solve management problem of supplier selection in two ways: aggregating individual decision maker’s opinion for each of the predefined criteria along with individual decision maker’s importance and ranking the suppliers based on both positive and negative ideal solutions using TOPSIS.

A robust framework incorporates not only suppliers’ performance but also provides weightage to key decision makers. Especially in the context of MCDMs wherein both qualitative and quantitative data is evaluated simultaneously, the proposed framework is unique in its practical implementation of reducing ambiguity in the supplier selection process.

The purpose of this paper is to assess the impact of deviation from the target investment in working capital (WC) (measured by net trade cycle (NTC)) on the profitability (measured by gross operating income (GOI) and net operating income (NOI)) of the listed non-financial Indian firms.

The study is based on the data collected on NTC, GOI, NOI and other variables pertaining to 242 listed non-financial Indian firms that form part of the Bombay Stock exchange 500 Index for the period 2012–2017 (1,452 firm-year observations). Following Banos-Caballero et al. (2010), the authors use a firm fixed effect regression as the benchmark regression for finding out the determinants of NTC of the sample firms. Furthermore, this study explores the impact of deviation (above and below target) from the target investments in WC on the firm profitability (GOI and NOI) employing fixed effect regression.

The result of this study reveals that Indian firms maintain a target NTC and try to converge in case of any deviations to it. Furthermore, the profitability of the sample firms was observed to be influenced by the deviation from the target NTC irrespective of whether the deviation was above or below the target investment level in WC.

This study highlights the importance of good WC management for firms due to the negative impact of the over- and under-investments in WC and contributes to the existing body of knowledge by suggesting that managers should keep close to the target WC and not deviate from this in order to maximize the firms’ profitability.

To the best of the knowledge of the researchers, this is perhaps the first study to examine the impact of firms’ deviation from their target investment in WC on the profitability for non-financial firms listed and operating in India.

Farmers producer organisations (FPOs) play the most crucial role in the agriculture supply chain system, aiming to redress the balance between farming and marketing activities of agricultural produce. The purpose of this study is to assess the performance of FPOs using data envelopment analysis (usually referred to as DEA) on 34 FPO units selected from the state of Rajasthan.

One of the most commonly used techniques to examine business performance is the application of DEA. The application of DEA requires the selection of inputs and outputs. This study takes three inputs and three outputs based on the insights drawn from the field survey. While the input variables consist of total assets, paid-up capital and the number of economic activities, the three output variables are turnover, net profit and number of members benefitted. Broadly, these variables encapsulate the operational performance of the business units.

This study’s findings reveal that the estimated relative efficiency score of the input-oriented CCR (Charnes, Cooper, and Rhodes) model ranges from 0.06 to 1. Interestingly, only one FPO has reported a relative efficiency (RE) score of one, whereas the remaining FPOs fall below the efficiency frontier. However, 15 FPOs report an RE score of one in the output-oriented CCR approach. Considering the estimates obtained in the input- and output-oriented BCC (Banker, Charnes and Cooper) models, this study found that about 20% of the FPOs report an efficiency score greater than 0.80. Moreover, three FPOs are on the frontier line. An examination of the scale efficiency score in the input-oriented model, 45% of the FPOs have an efficiency score greater than 0.80, whereas almost all FPOs achieve a scale efficiency score greater than 0.80 in the output-oriented model. Overall, the results imply that the FPOs should place greater emphasis on the efficient utilisation of the inputs to enhance the overall business performance and productivity.

The findings of this study provide vital insights into the specific inputs and outputs that determine the performance efficiency of FPOs and identify the potential areas for improving the existing inefficient FPOs.

This study contributes to the repository of the existing empirical studies in three distinct ways. First, the authors hardly found any previous studies that quantitatively assess the business performance of FPOs using the DEA technique. Second, the effort to identify the slacks associated with each input and output variable in input- and output-oriented models gives insights on improvable areas for inefficient FPOs. Third, the authors attempt to demystify the empirical obfuscations by highlighting the major challenges FPOs face in the state of Rajasthan.

The purpose of this study is to examine the effects of sensitization on the metallurgical characteristics of weld joints made up of austenitic stainless steel (AISI 316L) and ferritic stainless steel (AISI 430), using the gas tungsten arc welding (GTAW) process with ER316L filler wires.

A non-consumable tungsten electrode with a diameter of 1.6 mm was used during the GTAW procedure. The filler wire, ER316L, was selected based on the recommendation provided in literature. To explore the interconnections among the structure and properties of these weldments, the techniques including scanning electron microscopy and optical analysis have been used. In addition, the sensitization behaviour of the weldments was investigated using the double loop electrochemical potentio-kinetic reactivation (DLEPR) test.

Microstructural analyses revealed the occurrences of coarsened grains with equiaxed columnar grains and migrating grain boundaries in the weld zone. The results of the DLEPR test demonstrated that heat affected zone (HAZ) of AISI 430 was more susceptible to sensitization than HAZ of AISI 316L. Microstructure analysis also revealed the precipitation of large amounts of chromium carbide at the grain boundaries region of AISI 430 welded steel, causing more sensitization and, as a result, more failure or breaking at the side of AISI 430 weld in the dissimilar weldment of AISI 316L–AISI 430.

The present work has been carried out to determine the appropriate welding conditions for joining AISI 316L and AISI 430, as well as the metallurgical properties of the dissimilar weldment formed between AISI 316L and AISI 430. Owing to the difficulties in measuring the performance of these types of dissimilar joints given their unique mechanical and microstructural characteristics, research on the subject is limited.

The purpose of the study was to produce a healthier, convenient and traditional ready-to-eat (RTE) snack option with increased nutritional value, using spent hen meat, dietary fibre (DF) and simple technological methods. The product was designed to be stable without refrigeration and be easily adoptable by local self-help groups, rural women and youth and entrepreneurs in urban and semi-urban areas.

Conventional binder used for making snacks, i.e. rice flour was partially replaced by different sources of antioxidant DFs, i.e. oat flour (T₁ – 10%), finger millet flour (T₂ – 5%) and amaranth flour (T₃ –15%) to prepare spent hen snack sticks (SHSS). The snacks were then packaged in low density polyethylene (LDPE) pouches and evaluated for their storage stability at ambient temperature for a period of 35 days. Their physico-chemical, sensory and microbiological quality was evaluated at a regular interval of 7 days. The proximate composition of developed SHSS was compared to commercially available snack products (chakli/murukku – snacks without meat).

The fibre-enriched SHSS showed significant improvement in nutritive value, as they contained more fibre (p = 0.001) and protein (p = 0.029) than control SHSS. When compared to commercially available snack product SHSS showed three-fold significant increase in protein (p = 0.000) and ash content (p = 0.001) and only 11%–12% total fat as compared to 31% fat in the market-available product. The most acceptable treatment in terms of overall sensory quality and nutritional aspects was T₃; however, T₂ was more shelf-stable during the storage period. The study showed that fibre-enriched snacks can be stored at ambient temperature for up to 35 days without substantial loss in physico-chemical, sensory and microbial quality. Hence, substituting rice flour with DFs can lead to the development of products with better sensory attributes and improved functionality.

The simplicity of the product in terms of composition, machinery and low production costs makes it an easily adoptable one by small-scale entrepreneurs, especially those belonging to semi-urban areas.

Incorporation of spent hen meat, a relatively cheap but abundant source of protein, in RTE products can serve as an effective way to alleviate protein malnutrition, whereas addition of fibre further improves the functionality of the product. The methodology can be easily taken up by small-scale entrepreneurs and create a market for snack-based functional meat products.