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The aim of this paper is to develop a model for the prioritization of collusive behaviours within Indian food grain supply chain (FGSC) to enable government authorities, entrusted with the task of public distribution, to address those frauds based on their priority for making an existing supply chain more sustainable.

An interval 2-tuple linguistic Technique for Order Preference by Similarity to Ideal Solution (ITL-TOPSIS) method has been used to deal with the problem of prioritization of frauds under incomplete and uncertain information. Unlike traditional methods, this methodology offers an ability to make informed decisions, without loss of information, while factoring in various ambiguities.

The outcome indicates that the most severe fraud is adulteration, which adversely impacts the health of a person. Bogus Ration Card comes next, as it results into the distribution of grains to non-poor, ineligible population rather than the deserving beneficiaries. Next is diversion, where diverted food grains end up being sold at much higher rates than specified subsidized rates. Theft is least severe, as this would not affect FGSC much until done on large scale.

More decision-makers can be consulted to entertain more uncertainty and ambiguity. Also, a comparative study can be performed using different methodologies.

The proposed modelling could empower various governmental and non-governmental regulatory bodies in formulation of food policies to effectively tackle the problem of inappropriate delivery of food to the unintended population and to take necessary informed decisions for ensuring food security and safety to the society at large.

There is a dearth of studies related to the prioritization of frauds within FGSC. This research bridges the gap in literature by providing a decision-making framework for prioritizing collusive behaviour under ambiguous and uncertain information.

The aim of this paper is to provide an approach to analyze the performance of TV programs and to identify what can be done to improve them.

The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS), the Ng-model, Grey relational analysis (GRA), and principal component analysis (PCA) were applied to evaluate the programs, using audience, share, and duration as the performance criteria.

By comparing TOPSIS to the Ng-model, PCA, and GRA, we verified that SVD and bootstrap SVD TOPSIS provide a good balance between equal-weights TOPSIS and the other models. This is because SVD and bootstrap SVD TOPSIS break down the data to a higher degree, but are less impacted by outliers compared to the long tail models.

To determine which TV programs should be replaced or modified is a complex decision that has not been addressed in the literature. The advantage of using a multi-criteria decision-making (MCDM) approach is that analysts can choose as many criteria as they want to rank TV programs, rather than relying on a single criterion (e.g., audience, share, target rating point).

This work represents the first time that robust MCDM methodology is applied to an audience data set to analyze the performance of TV programs and to identify what can be done to improve them. This study shows the application of a detailed methodology that is useful for the improvement of TV programs and other entertainment industry content.

The main purpose of this paper is to conduct a review of the literature published on food supply chain management (FSCM) in last one and half decade to find out the ongoing research in the field, identify gaps and develop relevant research questions (RQs) from the perspectives of academicians, researchers, policymakers and corporate for the future research.

In all 281 research articles published on FSCM between the years 2005 and 2020 used for searching online databases such as Emerald, Science Direct (Elsevier), Springer and Wiley online. The methodology of structured review and classification involves various dimensions such as journal, publishing house, country, research design and methods, data analysis tool and multi-criteria decision-making methods.

It is found that the research in the field of FSCM has gained momentum in the last one and half decades. Majority of published articles are related to food supply chain management and food cold chain. Fewer authors have addressed issues and challenges related to food chain in developing country like India and still fewer studies are found on comparison of present food chain management practices adopted by developing countries like India vis-à-vis developed countries. Also it is observed that limited research is reported in food chain logistics system and intelligent tracking system.

This paper is limited to reviewing only those articles which are related to food chain management.

The main objective of this comprehensive review of literature is to present the various perspectives of food chain management and its numerous challenges. This paper attempts to draw the attention of researchers for further research in the FSCM disciplines. The findings provide future research directions, need of sound policymaking and regulatory mechanism to ensure food security to world's second largest populous country.

To assess the state of supply chain management (SCM) research in India and to understand the research trends and methodologies used. The present study also aims to create a taxonomy of the subject areas researched in India.

The present study employed the systematic literature review methodology. Literature from 395 peer journal papers in 67 leading journals over a 20-year period (2000–2020 Quarter-1) was comprehensively reviewed and assessed.

SCM research in India started around the year 2000. The quantum of research was low (single digit) until 2010. There has been steady growth over the last decade, and over 50% of the total papers up until now has been published in the last four years. The present study created a three-tiered taxonomy of the subject areas and classified the papers as per it. The first tier (level-1) has seven categories (SCM strategy, network design, SCM processes and integration, IT systems, skills, performance measurement and others). A perusal of the newly created taxonomy revealed that, except for a few areas under level-1 categories (such as SCM processes and SCM strategy), the other level-1 categories have not seen much research. Similarly, there is little or no research in a large number of level-2 categories (such as outsourcing strategy, channel strategy, demand management, demand fulfillment, customer relationship management, integrated supply chain planning, new product development, returns, supply chain orientation, performance monitoring, performance improvement, SCM adoption process, SCM implementation issues and quantified benefits of SCM). Methodologically, the rigor of SCM research in India needs improvement.

A comprehensive taxonomy of SCM subject areas researched in India at three cascading levels was created for the first time in the present study. The taxonomy will help provide researchers with a clear understanding of the structure of the subject areas and help in identifying areas where research has been carried out and the subject areas where gaps exist for future research to proceed. The present study also provides an overview of the methodological rigor of SCM research in India and points out some of the limitations that researchers should avoid in future studies.