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This study empirically investigates the interdependency of select Asian emerging economies along with the financial stress index during the times of the global financial crisis, the Euro crisis and the COVID-19 period. Moreover, it inspects the long-memory effects of the different crises during the study period.

To address the objectives of the study, the authors apply different statistical tools, namely the adjusted correlation coefficient, fractionally integrated generalised autoregressive conditional heteroskedasticity (FIGARCH) model and wavelet coherence model, along with descriptive statistics.

Financial stress is having a prodigious effect on the economic growth of select economies. From the data analysis, it is found that the long-memory effect is noted in the gross domestic product (GDP) for India and Korea only, which implies that the volatility in the GDP series for these two nations demonstrates persistence and dependency on previous values over a lengthy period.

The study is unique of its kind to consider multi-segments within the period of the study to get a clear idea about the effects of the financial stress index on select Asian emerging economies by applying different econometric tools.

This study aims to examine the Lumpkin and Dess (1996) conceptualization of entrepreneurial orientation (EO) in an emerging economy, focusing on India. It ascertains the dimensions of EO that are valuable in securing superior firm performance in emerging economies, which might differ from a developed market setting. It further examines the difference in the significance of dimensions between the manufacturing and services industry.

A novel primary data set consisting of responses from 228 new ventures incorporated in India was created through an online questionnaire survey following the tailored design method principles. A disaggregated approach was adopted and the data were analyzed using multiple regression in SPSS 21.

Among the dimensions of EO, competitive aggressiveness positively affected new venture performance, whereas proactiveness did not show any effect. Autonomy also exhibited a positive impact, except for new venture growth in manufacturing firms. Innovativeness exhibited partial support, only for the effectiveness of service firms. Risking-taking exhibited a negative effect on performance, particularly for manufacturing firms.

The findings guide entrepreneurs and managers operating their new ventures in emerging economies by suggesting the dimensions that are most likely to benefit firm performance and those that might be detrimental.

This study empirically validates the multidimensional conceptualization of EO in India and extends previous studies, which have typically focused on an aggregated EO scale. This study’s findings attest that the manifestation of EO in emerging economies might be different compared to mature economies. The contrast between the manufacturing and service sectors is also shown.

This paper aims to compute total factor productivity (TFP) growth for India as well as for its 19 major states and to explore the determinants of TFP at the state level by considering the spillover effects.

TFP growth has been obtained using growth accounting equation. Further, the TFP growth estimates were used to derive TFP levels using the translog index procedure. Given the policy focus on building infrastructure and expanding financial access, we have estimated the impact of irrigation, electricity, road, health, education and financial depth on TFP using the Spatial Durbin Model to account for spillover effects.

Computing TFP growth for two sub periods, namely, 2001-2008 and 2009-2015, the study finds a deterioration in TFP growth for India as well as for 10 of the 19 states under study in the post global financial crisis period. The author find that TFP is positively impacted by irrigation, health and road infrastructure. While financial depth and education were statistically insignificant, installed capacity of electricity had a negative impact on state level TFP.

'The author provides rationale for the empirical findings considering the country context. The findings of this study act as pointers for shaping higher growth on a sustained basis in India. The study helps to assess the productivity growth in the new states, namely, Jharkhand, Chhattisgarh and Uttarakhand, that were carved out in 2000 vis a vis their parent states. This assessment is useful especially for the states of Jharkhand and Chhattisgarh which were created to address economic backwardness in certain pockets of the parent states.

First, it provides TFPG estimates for India as well as 19 major states during the 2000-2015 period. Second, this study helps to understand how TFPG for India as well as each of the 19 states have behaved in the post global financial crisis period. Third, the study helps to assess the productivity growth in the three newly created states in 2000 vis a vis their parent states. Fourth, this is the first attempt which considers the spatial interdependence among the states to estimate the impact of financial and infrastructural development on productivity in the Indian states.

This paper introduces the concept of policy efficiency of banks as their efficiency in implementing the government's policies. It further compares the Indian public sector banks (PSBs) and private sector banks (PVBs) on two efficiency paradigms, operational efficiency and policy efficiency.

A three-stage analysis is carried out on data collected for 19 PSBs and 16 PVBs for ten years. Non-radial DEA with slack-based measure (SBM) is used to obtain efficiency scores of the banks for the two efficiency paradigms. The efficiency scores and the changes in efficiency and Malmquist index are further analysed by Tobit regression and seemingly unrelated regression (SUR) models.

PVBs are found to be more operationally efficient than PSBs. On the contrary, PSBs are found to be more policy efficient. Among the PSBs, the older and larger banks performed better in both the paradigms. Though Indian banks have become more operational and policy efficient over the years, the rate of improvement is slowing down.

Results imply that evaluating banks, especially PSBs, only on their operational efficiency is myopic. Their efficacies must also be measured by the roles they play on social and policy front. The loss of efficiency of Indian PSBs in a competitive environment should provoke thoughts of reforms. The study suggests that the proposed merger of PSBs to form large banks might be fruitful.

The study contributes to the literature by introducing the measure of policy efficiency. It shows that the Indian PSBs are indispensable as vehicles of government policy implementation.

This paper aims to find the minimum possible number of phasor measurement units (PMUs) to achieve maximum and complete observability of the power system and improve the redundancy of measurements, in normal cases (with and without zero injection bus [ZIB]), and then in conditions of a single PMU failure and outage of a single line.

An efficient approach operates adequately and provides the optimal solutions for the PMUs placement problem. The finest function of optimal PMUs placement (OPP) should be mathematically devised as a problem, and via that, the aim of the OPP problem is to identify the buses of the power system to place the PMU devices to ensure full observability of the system. In this paper, the grey wolf optimizer (GWO) is used for training multi-layer perceptrons (MLPs), which is known as Grey Wolf Optimizer (GWO) based Neural Network (“GW-NN”) to place the PMUs in power grids optimally.

Following extensive simulation tests with MATLAB/Simulink, the results obtained for the placement of PMUs provide system measurements with less or at most the same number of PMUs, but with a greater degree of observability than other approaches.

The efficiency of the suggested method is tested on the IEEE 14-bus, 24-bus, New England 39-bus and Algerian 114-bus systems.

This paper proposes a new method for placing PMUs in the power grids as a multi-objective to reduce the cost and improve the observability of these grids in normal and faulty cases.

The purpose of this study was to assess the preservative potential of Tinospora cordifolia as a novel natural preservative in muscle foods.

Chevon sausages were used as a model system and were prepared by incorporating different levels of T. cordifolia, namely, T1 (0.25 per cent), T2 (0.50 per cent) and T3 (0.75 per cent), and assessed for lipid oxidative stability and storage quality under refrigerated (4 ± 10°C) conditions.

Lipid oxidative stability showed a significant improvement as the products incorporated with T. cordifolia exhibited significantly (p = 0.001) lower thiobarbituric acid reacting substances (mg malonaldehyde/kg) in comparison to control. A significant improvement was also observed in the microbial stability as T. cordifolia-incorporated products showed significantly lower values for total plate count (log cfu/g, p = 0.001), psychrophilic count (log cfu/g, p = 0.003), yeast and mould count (log cfu/g, p = 0.02) and free fatty acid (percentage of oleic acid, p = 0.01). Significantly higher scores were observed for various sensory parameters of the treated products during storage.

Tinospora cordifolia successfully improved the lipid oxidative and microbial stability of the model meat product and may be commercially exploited as a novel preservative in muscle foods.