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The coronavirus (COVID-19) is the worst pandemic in recent memory in terms of its economic and social impacts. Deadly second wave of COVID-19 in India shook the country and reshaped the ways organizations functions and societies behave. Medical infrastructure was unaffordable and unsupportive which created high distress in the Indian society, especially for poor. At this juncture, some pharmaceutical firms made a unique social investment when they reduced price of drugs used to treat COVID-19 patients. This study aims to examine how the market and the society respond to the price reduction announcement during the psychological distress of COVID-19.

Market reactions have been analyzed by conducting an event study on stock market data and visual analytics-based sentiment analysis on Twitter data.

Overall, this study finds positive abnormal returns on the day and around the day of event. Interestingly, this study finds that returns during the time of high distress are significantly higher. Sentiment analysis conveys that net sentiment is favorable to the pharmaceutical firms around the day of event and it sustains more during the time of high distress.

This study is unique in contributing to the business and industrial management literature by highlighting market reactions to social responsibility of business during the time of psychological distress in emerging economies.

Vaccine hesitancy is a long-standing issue among both the general population and health communicators. This study aims to ascertain the inclination and the reasons for vaccine hesitancy by conducting content analysis and sentiment analysis of the perspectives expressed in comments on videos related to vaccine hesitancy uploaded from India on YouTube.

The assessment of the sentiments of the vaccine-hesitant population is done using Valence Aware Dictionary and sEntiment Reasoner sentiment analysis module implemented with Python’s NLTK library to automatically determine the sentiments of the comments. Manual content analysis was performed on 60.09% viewer comments randomly selected from the total comments in 238 videos on vaccine hesitancy originated from India and labelled each comment with labels “Anti”, “Pro”, “Confused”, “Not Applicable” and “Unrelated” labels.

The study found “Mistrust-Government policies”, “Fear-health related consequences”, “Mistrust-Scientific research”, “Vaccine effectiveness and efficacy” and “Misinformation/myths” as the top five determinants for vaccine hesitancy, whereas “Religious beliefs”, “Fear-Economic consequences”, “Side Effects- short-term” and “Fear-mode of administration” found to be the lesser cited reasons for vaccine hesitancy. However, the study also investigates changes in the inclination of Indian commenters towards vaccine hesitancy and revolving issues over time.

Public health policymakers and health communicators may find the study useful in determining vaccine hesitancy factors in India.

The originality of this study lies in its approach. To date, no sentiment analysis has been conducted on the content released on YouTube by Indian content creators regarding pro- and anti-vaccination videos. This inquiry seeks to fill this research gap.

The academic literature has examined why bank runs happen based on the work of 2022 Nobel Prize-winning economists Diamond and Dybvig. They have found the source of banking/financial crisis in terms of mismatch between liabilities (deposits being short term and savers wanting to short-term access to their money) and assets (long term and illiquid). The Lakshmi Vilas Bank (LVB) crisis intensified when it came under Prompt Corrective Action (PCA) of the Reserve Bank of India (RBI). This situation provides the opportunity to study whether the elements embodied in the theoretical models like Diamond and Dybvig hold true for LVB crisis. This study aims to examine the reasons for the demise of LVB in India using DuPont financial model, peer group analysis and time series structural break in crucial financial parameters.

The study examines the reason for insolvency of LVB using financial ratios, financial models (DuPont), financial distress model (Z-score) and asset-liability management. The study also adopts univariate structural break models using quarterly financial data covering the key financial measures used in the RBI’s PCA framework.

LVB crisis is like Diamond–Dybvig model, in the sense, savers requiring short-term access to their money (liquidity for their deposits) on the information of high non-performing assets, which further deteriorates the illiquid nature of loan portfolio (assets) of banks. The study finds its profit margin (net interest margin and non-interest margin) and managerial efficiency had started deteriorating since 2018. The study finds that LVB’s main weakness lies in its limited credit appraisal ability, its monitoring and weak internal controls. Lending to sensitive sectors (like real estate, capital markets and commodities) and exposure to large business groups also contributed to its weakness. The study also finds huge, elevated asset-liability mismatch, especially in the short-term maturity buckets. Using univariate econometric time series model, the study also confirms financial weakness being evident much earlier than the time when resolution was undertaken by the RBI through PCA.

The study has implications for analysing and monitoring financial distress of banks. The study also has implications for devising banking regulation and supervision.

The study brings in a perspective of the banking regulations using the application of PCA framework on a listed private sector bank. The authors combine an accounting ratio model and combine risk measures that could identify the incipient risks in a bank. The authors believe this will help in refinement of banking regulations and better monitoring mechanisms.

The study aims to explore the savings behaviour of Indian farmers. An attempt is also made to inspect the effect of financial literacy (FL) and financial confidence (FC) on the savings behaviour of the farmers in India.

This study used secondary data on 10,263 Indian farmers from Financial Inclusion Insights, 2017 database. Relevant statistical techniques and ordered probit regression were used to unfold the effect of FL and FC on the savings behaviour of farmers.

The outcome of the study revealed that the majority of the Indian farmers exhibited poor levels of FL and FC. Of the total, 42.99% were found to save regularly. FL and FC were observed to play instrumental roles in steering the savings behaviour of the Indian farmers. Household size, financial shocks, gender, farm ownership, income, household financial decision-making process, religion and educational attainment have emerged to be significant predictors of the savings behaviour of Indian farmers.

The present study makes an original contribution to the extant literature by unfolding the savings behaviour of Indian farmers and the effect of FL and FC on such behaviour using a rich sample of 10,263 farmers for the first time.

An integrated intuitionistic fuzzy (IF) modelling-based framework for examining the performance analysis of a packaging unit (PU) in three different stages has been proposed.

For the series and parallel configuration of PU, a mathematical model based on the intuitionistic fuzzy Lambda–Tau (IFLT) approach was developed in order to calculate various reliability parameters at various spreads. For determining membership and non-membership function-based reliability parameters for the top event, AND/OR gate transitions expression was employed.

For 15%–30% spread, unit’s availability for the membership function falls by 0.006442%, and it falls even more by 0.014907% with an increase in spread from 30% to 45%. In contrast, for 15%–30% spread, the availability of non-membership function-based systems reduces by 0.007491% and further diminishes. Risk analysis has presented applying an emerging approach called intuitionistic fuzzy failure mode and effect analysis (IFFMEA). For each of the stated failure causes, the output values of the intuitionistic fuzzy hybrid weighted Euclidean distance (IFHWED)-based IFFMEA have been tabulated. Failure causes like HP1, MT6, FB9, EL16, DR23, GR27, categorized under subsystems, namely hopper, motor, fluidized bed dryer, distributor, grader and bin, respectively, with corresponding IFFMEA output scores 1.0975, 1.0190, 0.8543, 1.0228, 0.9026, 1.0021, were the most critical one to contribute in the system’s failure.

The limitation of the proposed framework lies in the fact that the results obtained for both reliability and risk aspects mainly depend on the correctness of raw data provided by the experts. Also, an approximate model of PU is obtained from plant experts to carry performance analysis, and hence more attention is required in constructing the model. Under IFLT, reliability parameters of PU have been calculated at various spreads to study and analyse the failure behaviour of the unit for both membership and non-membership function in the IFS of [0.6,0.8]. For both membership- and non-membership-based results, availability of the considered system shows decreasing trend. To improve the performance of the considered system, risk assessment was carried using IFFMEA technique, ranking all the critical failure causes against IFHWED score value, on which more attention should be paid so as to avoid sudden failure of unit.

The livelihood of millions of farmers and workers depends on sugar industries. So perpetual running of these industries is very important from this viewpoint. On the basis of findings of reliability parameters, the maintenance manager could frame a correct maintenance policy for long-run availability of the sugar mills. This long-run availability will generate revenue, which, in turn, will ensure the livelihood of the farmers.

Mathematical modelling of the considered unit has been done applying basic expressions of AND/OR gate. IFTOPSIS approach has been implemented for ranking result comparison obtained under IFFMEA approach. Eventually, sensitivity analysis was also presented to demonstrate the stability of ranking of failure causes of PU.

To meet energy demand and tackle the challenges posed by global warming, Bagasse-based Cogeneration Power Generation (BCPG) plant in sugar mills have tremendous potential due to large-scale supply of renewable fuel called bagasse. To meet this goal, an integrated framework has been proposed for analyzing performance issues of BCPG.

Intuitionistic Fuzzy Lambda-Tau (IFLT) approach was implemented to compute various reliability parameters. Intuitionistic Fuzzy Failure Mode and Effect Analysis (IF-FMEA) approach has been implemented for studying risk issues results in decrease in plant's availability. Moreover, IF- Technique for Order Performance by Similarity to Ideal Solution (IF-TOPSIS) is implemented to verify accuracy of IF-FMEA approach.

For membership and non-membership functions, availability decreases to 0.0006% and 0.0020% respectively for spread ±15% to ±30%, and further decreases to 0.0127% and 0.0221% for spread ±30% to ±45%. Under risk assessment failure causes namely Storage tank (ST3), Valve (VL6), Transfer pump (TF8), Deaerator tank (DT11), High pressure heater and economiser (HP15), Boiler drum and super heater (BS22), Forced draft and Secondary air fan (FS25), Air preheater (AH29) and Furnace (FR31) with Intuitionistic Fuzzy Hybrid Weighted Euclidean Distance (IFHWED) based output scores – 0.8988, 0.9752, 0.9400, 0.8988, 0.9267, 1.1131, 1.0039, 0.8185, 1.0604 were identified as the most critical failure causes.

Reliability and risk analysis results derived from IFLT and IF-FMEA approaches respectively, to address the performance issues of BCPG is based on the quantitative and qualitative data collected from the industrial experts and maintenance log book. Moreover, to take care of hesitation in expert's knowledge, IF theory-based concept is incorporated so as to achieve more accuracy in analysis results. Reliability and risk analysis results together will be helpful in analyzing the performance characteristics and diagnosis of critical failure causes, which will minimize frequent failure in BCPG.

The framework will help plant managers to frame optimal maintenance policy in order to enhance the operational aspects of the considered unit. Moreover, the accurate and early detection of failure causes will also help managers to take prudent decision for smooth operation of plant.

The results obtained ensure continuous operation of plant by utilizing the bagasse as fuel in boiler and also mitigate the wastages of fuel. If this bagasse (green fuel) is not properly utilized, there remains a dependency on coal-based power plants to meet the power demand. The results obtained are useful for decreasing dependency on coal, and promoting bagasse as the green, and alternative fuel, the emission by burning of these fuels are not harmful for environment and thereby contribute in preventing the environment from harmful effect of GHGs gases.

IFLT approach has been implemented to develop reliability modeling equations of the BCPG unit, and furthermore to compute various reliability parameters for both membership and non-membership function. The ranking results of IF-FMEA are compared to IF-TOPSIS approach. Sensitivity analysis is done to check stability of proposed framework.

This paper proposes a framework for the implementation of sustainability practices by individual companies and corresponding supply chains (SCs), considering the various SC tiers, the three dimensions of sustainability and the following critical areas: Governance, Product and Process, Customers and Suppliers Management, and Stakeholder focus.

Using several case studies of small- and medium-size companies, a qualitative methodology is used to develop the proposed framework.

The analysis of these case studies makes it possible to identify the sustainability practices that are the most important for practitioners, thereby reducing the number of sustainability practices specified in the literature and giving some insights regarding which should be used in addressing critical areas. A set of guidelines and actions is also suggested for managers to continue the path of sustainability.

Further studies in other cultural and national realities and industrial contexts are desirable to assess the proposed framework's suitability and the results obtained.

The results of this study show that the practices implemented are highly dependent on the resources that the company can mobilize and, on the choices, and commitment to sustainability on the part of top management.

The authors propose a framework to help individual companies and corresponding SCs to implement sustainability practices considering the various dimensions of sustainability, critical areas and SC's various partners.

This study aims to investigate the optimal process parameters of the wire-cut electrical discharge machining (WCEDM) for the machining of the GZR-AA7475 hybrid metal matrix composite (HMMC). HMMCs are prepared with 2 Wt.% graphite and 4 Wt.% zirconium dioxide reinforced with aluminium alloy 7475 (GZR-AA7475) composite by using the stir casting method. The objective is to enhance the mechanical properties of the material while preserving its unique features. WCEDM with a 0.18 mm molybdenum wire electrode is used for machining the composite.

To conduct experimental studies, a Taguchi L27 orthogonal array was adopted. Input variables such as peak current (I_p), pulse-on-time (T_ON) and flushing pressure (P_F) were used. The effect of process parameters on the output responses, such as material removal rate (MRR), surface roughness rate (SRR) and wire wear ratio (WWR), were investigated. The grey relational analysis (GRA) is used to obtain the optimal combination of the process parameters. Analysis of variance (ANOVA) was also used to identify the significant process parameters affecting the output responses.

Results from the current study concluded that the optimal condition for grey relational grade is obtained at T_ON = 105 µs, I_p = 100 A and P_F = 90 kg/cm². Peak current is the most prominent parameter influencing the MRR, whereas SRR and WRR are highly influenced by flushing pressure.

Identifying the optimal process parameters in WCEDM for machining of GZR-AA7475 HMMC. ANOVA and GRA are used to obtain the optimal combination of the process parameters.

This study aims to address the current gap in knowledge of indirect procurement performance management. It attempts to argue the need for a specific and tailored performance management approach for the indirect procurement function that incorporates a balanced approach, beyond financial measures.

The case study approach evaluated key performance indicators from a balanced scorecard (BSC) perspective in the development of a performance measurement system (PMS) for a Middle Eastern university’s indirect procurement division. It initially reviewed the literature to assess potential indicators for this context. It used vision and mission statement analysis alongside expert interviews to augment the literature. The candidate indicators were then evaluated and ranked by an expert panel through applying a four-round Delphi technique.

Twenty-nine procurement-specific indicators are suggested in a BSC framework. The five highest-ranked indicators were not in the financial perspective unlike other BSC studies in the broader field of supply chain management (SCM).

The study suggests a framework and indicators for a procurement PMS for practitioners to consider. It also highlights there is no one-size-fits-all and that organisations need to tailor PM to the organisation and divisional strategy and operational needs. This study aids the development of guidelines for executives and procurement management that wish to develop indicators and a PMS.

This study contributes to knowledge by partly addressing the under-researched field of indirect procurement PM. The literature suggested that various roles in SCM require specific PM indicators. This study puts forward a BSC framework with 29 indicators specifically for indirect procurement. Fourteen of these indicators were derived from non-literature sources. This study enhances knowledge and contributes to the limited debate and evidence on indirect procurement PM and the broader PM literature.

This study explores the relevance of film texts in Indian social studies classrooms for students at the upper primary level. It examines how different types of visual texts can facilitate awareness, critical thinking, discussion and action.

Using multimodal discourse analysis (MDA), this paper critically evaluates five selective films from regional cinemas in India and explores their teaching implications for social studies. The study argues that films are vital multimodal resources that can challenge the prevailing narratives in social studies pedagogy. It conveys how the suggestive revised taxonomy could benefit the students. It proposes a classification system for film analysis with discussion and states how films can bring out interrelated themes and encourage deeper, critical inquiry within the curriculum. The study finds discourse around the films and qualitatively stresses dialogue exchange with sentiment analysis using MAXQDA software. Developed by VERBI software, MAXQDA is a product whose name is inspired by the German Sociologist Max Weber, while the ‘QDA' stands for Qualitative Data Analysis.

The films act as multimodal texts, navigators, metaphors, communicative circuits and catalysts. The paper concludes that films can improve and expand multimodal learning of social studies in three ways: films help learners connect emotionally with the concepts, films make the learning process more appealing and extend it beyond classroom boundaries and films offer a unique insight into the socio-cultural subtleties that are often limited in textbooks.

This research pioneers an intersectionality-driven framework for film analysis in the curriculum for Indian upper primary social studies, offering innovative pedagogical tools to enrich Indian curriculum insights and bridge existing knowledge gaps.