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Starchy foods have been emphasized in the diet for reducing hyperglycemia and hyperinsulinemia. However, all starch containing foods respond differently, depending upon various other factors in food such as the amylose:amylopectin ratio, co‐ingredients, methods of cooking, etc. which also impact its metabolic response. During days of fast, in India, potato and sago are the most commonly used food to provide quick source of energy. The purpose of this paper is to determine the functional and nutritional quality of fasting foods such as potato and sago, having higher amylopectin content, with respect to their relative glycemic and insulin response in normal healthy volunteers.

The postprandial glycemic response to boiled potato and sago khichdi in relation to equal quantity of bread (reference) was compared using Relative Glycemic Potency (RGP) represented as the Glycemic Bread Equivalent (GBE) of foods. Five clinically healthy subjects were fed 100 g of test foods and standard, and their blood glucose and insulin response was recorded at fasting (0 min) and at 30, 60, 90 and 120 min.

It was found that both potato and sago khichdi produced peak glucose response at 30 min and levels returned to baseline within 60 min. The higher amylopectin content which facilitates faster absorption from the gastro‐intestinal tract and into the cell results in the total area under the curve (AUC) glycemic response to potato and sago khichdi to be significantly lower than that of bread (p < 0.05). The total AUC insulin response to potato (p <0.05) and sago khichdi was also lower than that of bread.

Therefore, starch‐based foods rich in amylopectin lead to quicker absorption of sugar to supply the energy to the energy‐deprived cells common in fasting condition.

The paper shows that the starch present in these fasting foods is typically characterized by a higher amylopectin:amylose ratio.

Rice is considered a high glycemic index food. However, the overall glycemic response to whole foods differs based on the presence of co‐components, cooking or processing technique, starch composition, and amount of food consumed. The purpose of this paper is to observe the relative glycemic impact (RGI) of foods based on postprandial glycemic response to equal quantities of test foods and standard‐bread expressed as glycemic bread equivalent (GBE), using rice and its products.

In total, five clinically healthy adult volunteers were fed 50 g test foods and bread on different days after an overnight fast. Blood sugar and insulin levels at fasting state and at 30, 60, 90 and 120 min after consuming food were recorded and corresponding area under the curve was calculated.

The GBE was highest for puffed rice at 107 g, whereas same amount of rice kheer and plain boiled rice induced glycemic response equivalent to 19.5 g and 11 g of bread, respectively. RGI of puffed rice was found to be significantly higher than that of rice kheer and boiled rice (p<0.01). Similarly, the total insulinemic effect of puffed rice (71 g) was found to be significantly higher than that of rice (6 g, p<0.01) and rice kheer (19 g, p<0.05).

Despite being prepared from common raw ingredient, all the three test foods produced varied glycemic and insulin responses. This can be attributed to the different processing conditions, change in nutrient composition and total quantity consumed.

The GBE values may constitute a simple and easy‐to‐use tool for consumers to select food in terms of their predicted glycemic and insulin responses, especially in the diabetic or insulin‐resistant group.

E-healthcare has gained importance, particularly in emerging economies, because of its ability to provide health-care products and services while minimizing contact with the external world, which was particularly relevant during the COVID-19 pandemic. Despite its advantages, consumers seem hesitant to use mobile apps to access such services. Previous research has found that perceived usefulness, time consumption and price significantly impact consumer willingness to purchase e-healthcare products on mobile apps. This study aims to investigate the role of consumer trust in the willingness to purchase e-healthcare products on mobile apps while controlling for the effects of perceived usefulness, time consumption and price.

Data have been collected using non-probability judgmental and snowball sampling techniques from five major cities in India. After the data cleaning process, 238 questionnaires were used for data analysis in this study. The authors used confirmatory factor analysis to validate all the constructs and subsequently used the hierarchical regression technique to conduct this study.

The study’s findings show that consumer trust is the most crucial factor for predicting a willingness to purchase e-healthcare products through mobile apps, despite several other variables that also have a positive impact. These findings present important practical implications for mobile app developers, health-care professionals and lawmakers to further enhance the adoption of e-healthcare products on mobile apps.

The research was conducted by considering primarily young adults (those between the ages of 20 and 45 – above) and targeted five cities in India. This highlights a limitation in the research, as small groups of the intended audience were included (mainly young people).

This study considers perceived usefulness, time and price, in addition to trust, to predict consumer willingness to purchase. Its findings can be valuable in the fields of consumer behavior, health care and technology, especially in emerging markets.

Given the dearth of thorough summaries in the literature, this systematic review and bibliometric analysis attempt to take a meticulous approach meant to present knowledge on the constantly developing subject of stock market volatility during crises. In outline, this study aims to map the extant literature available on stock market volatility during crisis periods.

The present study reviews 1,283 journal articles from the Scopus database published between 1994 and 2022, using the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) 2020 flow diagram. Bibliometric analysis through software like R studio and VOSviewer has been performed, that is, annual publication trend analysis, journal analysis, citation analysis, author influence analysis, analysis of affiliations, analysis of countries and regions, keyword analysis, thematic mapping, co-occurrence analysis, bibliographic coupling, co-citation analysis, Bradford’s law and Lotka’s law, to map the existing literature and identify the gaps.

The literature on the effects of crises on volatility in financial markets has grown in recent years. It was discovered that volatility intensified during crises. This increased volatility can be linked to COVID-19 and the global financial crisis of 2008, as both had massive effects on the world economy. Moreover, we identify specific patterns and factors contributing to increased volatility, providing valuable insights for further research and decision-making.

The present study is confined to the areas of economics, econometrics and finance, business, management and accounting and social sciences. Future studies could be conducted considering a broader perspective.

Most of the available literature has focused on the impact of some particular crises on the volatility of financial markets. The present study is not limited to some specific crises, and the suggested research directions will serve as a guide for future research.