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The purpose of this paper is to identify various risk drivers which affect a food processing supply chain and to create a map of how those risk drivers propagate risks through the supply chain and impact important performance measures.

This study involves experts from food processing companies to elucidate the contextual relationships among the risk drivers and between risk drivers and performance measures. This is used to quantify the relationships and to determine the indirect and overall relationships applying Fuzzy Interpretive Structural Modeling.

Three categories of risk drivers which Indian food processing companies need to pay maximum attention to minimize risks are identified. These are supplier dependency and contracting, supplier variability, visibility and traceability and manufacturing disruptions. Analysis shows that collaborating with suppliers and logistics service providers, developing mutually beneficial contracts with them while ensuring that adequate technology investments are made can significantly mitigate risks and consequently improve margins and lead to revenue growth.

This study has been carried out with experts from large food processing companies in India, and hence, the results cannot be generalized across other types of food processing companies.

The proposed methodology can help understand the interrelationships between supply chain risks and between those risks and performance measures. Thus, it can help a food processing company to create business cases for specific supply chain risk mitigation projects.

This study is one of the earliest to create a comprehensive risk propagation map for food processing companies which helps in quantifying the impact the risk drivers have on each other and on performance measures.

A woman's nutritional status significantly determines her overall well-being. The authors critically examine the trends — including socioeconomic disparities — in undernutrition among Muslim women in India, a notably socio-economically disadvantaged group. The authors also investigate trends and variations across the dimensions of caste, place of residence (rural/urban), education, economic status and geographic regions.

The analysis leverages the nationally representative National Family Health Surveys (NFHS) of India conducted between 1998 and 2021. The authors examined poor–rich ratios, concentration indices, disparity ratios and predicted probabilities of being underweight (captured using Body Mass Index).

From 1998 to 2021, there has been a decline in undernutrition prevalence among Muslim women. However, stark socioeconomic variations persist. While the prevalence has decreased over time across all socioeconomic groups, disparities — both within and between groups — remain significant and, in many cases, have expanded. For certain socioeconomic subgroups (e.g. Muslim women with no formal education or those in the Central and Northeast regions), the disparity doubled between 1998 and 2021. In regions like the South, where undernutrition prevalence is low or has reduced, disparities remain significant and generally have increased.

To the authors’ knowledge, the study is the first to provide a comprehensive examination of the prevalence, trends and socioeconomic disparities in undernutrition among Muslim women in India over the past two decades.

The peer review history for this article is available at: https://publons.com/publon/10.1108/IJSE-04-2023-0320