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Given the promising growth of digital payments in India, this study aims to identify motivational factors influencing digital payment acceptance among Indian consumers and how consumers perceive these services when segregated by demographic profiles of gender, age, education and income levels. An online survey targeting 386 respondents was targeted to study the key determinants of digital payments adoption. The study reveals that trust, subjective norm, perceived risk, ease of use, and usefulness are key predictors of digital payment adoption. In addition, invariance analysis provides empirical evidence of scale non-invariance when consumers are segregated by gender and education. The study is pioneering in digital payments as useful insights are gained, which can help policymakers and service providers design future strategies for wider acceptance of digital payments. [ABSTRACT FROM AUTHOR]

The first law of thermodynamics involves several types of energies and many studies have shown that students lack awareness of them. They have difficulties in applying the law to different thermodynamic processes. These observations were confirmed in our pilot studies, carried out with students from undergraduate colleges across the whole of India. We, then, decided to develop an activity-based module to address students' conceptual difficulties in this area. In particular, we took up the cases of both adiabatic and isothermal compression of an ideal gas. We tested, through a two-group pre and post test design, the effectiveness of the module.

Heat and thermodynamics is a conceptually rich area of undergraduate physics. In the Indian context in particular there has been little work done in this area from the point of view of misconceptions. This prompted us to undertake a study in this area. We present a study of students' misconceptions about heat transfer mechanisms, i.e. conduction, convection and radiation, and about elementary kinetic theory. (Contains 5 figures.)

The increasing participation of retail investors — generally having limited risk bearing ability — in mutual funds, has surprisingly not motivated rigorous examination of downside risks-forward return relationship of these funds, which this study aims to accomplish. We use a survivorship-bias free database of returns and portfolio holdings of Indian equity mutual funds covering the period April 2008–November 2018 with Cornish–Fisher expansion of Value-at-Risk (VaR) as a measure of downside risk to examine downside risk-forward return relationship controlling for the fund characteristics such as age, size and style. To complete the story, we also test for the presence of Downside Risk Timing (DRT) ability of fund managers. We find that downside risk does predict future returns of mutual funds and the result holds across different fund sizes, age and styles, particularly strongly in large and midcap style. We also find that the fund manager of the median fund exhibits positive DRT at the 1- and 6-month horizons and negative at the 3- and 12-month horizons. The mixed evidence on DRT suggests that fund managers either did not possess the requisite risk-timing ability or had failed in its application. Findings have important implications for both investors and fund managers. [ABSTRACT FROM AUTHOR]

Phytoplankton functional‐type (PFT) data are assimilated into the global coupled ocean‐ecosystem model MITgcm‐REcoM2 for two years using a local ensemble Kalman filter. The ecosystem model has two PFTs: small phytoplankton (SP) and diatoms. Three different sets of satellite PFT data are assimilated: Ocean‐Color‐Phytoplankton Functional Type (OC‐PFT), Phytoplankton Differential Optical Absorption Spectroscopy (PhytoDOAS), and SYNergistic exploitation of hyper‐ and multi‐spectral precursor SENtinel measurements to determine Phytoplankton Functional Types (SynSenPFT), which is a synergistic product combining the independent PFT products OC‐PFT and PhytoDOAS. The effect of assimilating PFT data is compared with the assimilation of total chlorophyll data (TChla), which constrains both PFTs through multivariate assimilation. While the assimilation of TChla already improves both PFTs, the assimilation of PFT data further improves the representation of the phytoplankton community. The effect is particularly large for diatoms where, compared to the assimilation of TChla, the SynSenPFT assimilation results in 57% and 67% reduction of root‐mean‐square error and bias, respectively, while the correlation is increased from 0.45 to 0.54. For SP the assimilation of SynSenPFT data reduces the root‐mean‐square error and bias by 14% each and increases the correlation by 30%. The separate assimilation of the PFT data products OC‐PFT, SynSenPFT, and joint assimilation of OC‐PFT and PhytoDOAS data leads to similar results while the assimilation of PhytoDOAS data alone leads to deteriorated SP but improved diatoms. When both OC‐PFT and PhytoDOAS data are jointly assimilated, the representation of diatoms is improved compared to the assimilation of only OC‐PFT. The results show slightly lower errors than when the synergistic SynSenPFT data are assimilated, which shows that the assimilation successfully combines the separate data sources. Key Points: Phytoplankton‐type assimilation corrects the phytoplankton fields stronger than total chlorophyll assimilation in particular for diatomsThe phytoplankton‐type assimilation reduces the exclusion of the different groups so that both types coexistThe joint assimilation of two phytoplankton‐type satellite products leads to further improvement of the assimilation results [ABSTRACT FROM AUTHOR]

This paper examines the role of macroeconomic news surprises on returns volatility of Indian Index futures market. Empirical literature posits that news arrivals have an influential impact on asset returns and returns volatility. Consistent with this proposition, we have undertaken a comprehensive examination to understand the relationship between macroeconomic news releases, trading volume, and returns volatility in an emerging financial market like India. Using high-frequency data sampled at 1-minute interval along with a broader class of macroeconomic news, we found that macroeconomic news surprises significantly affect both returns volatility and trading volume and that the response of Index futures contract to macroeconomic news surprise is rather swift and significant. Further, there is evidence that several macroeconomic news surprises seemingly exhibit asymmetric impact on the Index futures contract. [ABSTRACT FROM AUTHOR]

The coupled ocean circulation‐ecosystem model MITgcm‐REcoM2 is used to simulate biogeochemical variables in a global configuration. The ecosystem model REcoM2 simulates two phytoplankton groups, diatoms and small phytoplankton, using a quota formulation with variable carbon, nitrogen, and chlorophyll contents of the cells. To improve the simulation of the phytoplankton variables, chlorophyll‐a data from the European Space Agency Ocean‐Color Climate Change Initiative (OC‐CCI) for 2008 and 2009 are assimilated with an ensemble Kalman filter. Utilizing the multivariate cross covariances estimated by the model ensemble, the assimilation constrains all model variables describing the two phytoplankton groups. Evaluating the assimilation results against the satellite data product SynSenPFT shows an improvement of total chlorophyll and more importantly of individual phytoplankton groups. The assimilation improves both phytoplankton groups in the tropical and midlatitude regions, whereas the assimilation has a mixed response in the high‐latitude regions. Diatoms are most improved in the major ocean basins, whereas small phytoplankton show small deteriorations in the Southern Ocean. The improvement of diatoms is larger when the multivariate assimilation is computed using the ensemble‐estimated cross covariances between total chlorophyll and the phytoplankton groups than when the groups are updated so that their ratio to total chlorophyll is preserved. The comparison with in situ observations shows that the correlation of the simulated chlorophyll of both phytoplankton groups with these data is increased whereas the bias and error are decreased. Overall, the multivariate assimilation of total chlorophyll modifies the two phytoplankton groups separately, even though the sum of their individual chlorophyll concentrations represents the total chlorophyll. Plain Language Summary: Different types of plankton are simulated globally with ocean ecosystem models. To further increase their prediction quality, we combine the model with satellite observations of chlorophyll using modern methods called data assimilation. This method allows us not only to improve the modeled total chlorophyll but also the simulation of the different plankton types. Further, we can fill gaps in the satellite data that results, for example, from clouds. Thus, we are able to better predict the ocean ecosystem, which in turn helps to understand climate change patterns and carbon cycle processes. Key Points: Multivariate assimilation of satellite chlorophyll data improves simulation of phytoplankton functional groups and influences them differentlySmall phytoplankton is weakly deteriorated in the Southern Ocean, while diatoms are improved globallyRegional variability of assimilation leads to stronger improvement at midlatitudes and equator than at high latitudes [ABSTRACT FROM AUTHOR]