Search results

The purpose of this paper is to harness the potential of microwave pre-treatment to prepare carbon from locally available Sterculia foetida fruit shells for adsorption of heavy metals, particularly Nickel ions (Ni++), from effluent.

The pre-treatment methods comprise conventional methods as sun drying and oven drying as well as high intensity microwave drying. Response surface methodology was employed to analyse the optimization of the process. The adsorption behavioural characteristics of the material were established applying adsorption isotherms.

Adsorption of Ni++ was found to be effective in microwave drying at output power of 300 W. It was observed that the maximum adsorption capacity was attained at pH 6; an adsorbent dosage of 0.25 mgml−1 and initial metal ion concentration of 20 ppm with an interactive effect of initial concentration and dosage.

The research puts emphasise on prospecting of novel biomass for carbonization and application of the same for effective adsorption. Available literature on Sterculia foetida is very limited and this work will serve to create database on the amenability of processing.

The results of the corrosion studies on mild steel in aqueous solutions containing 0.5 to 100 ppm of S= either in inactive or radioactive Na2S for an immersion period of 24 hours, show that rusting of mild steel surface appeared at the S= concentrations of 5 and 10 ppm, staining of surface at 25 ppm and pitting at 50 and 100 ppm. Under similar conditions, the studies on mild steel in Na2CrO4 (0.0025 M, 0.005 M) solutions containing varying concentrations of inactive or radioactive S= (0.5 to 150 ppm) indicate that rusting/staining/pitting on mild steel surface did not occur even at higher concentrations of S=. In aqueous solutions containing 0.5 to 100 ppm of S= either in radioactive or inactive Na2S, the open circuit potential shifted towards less noble values, whereas in Na2CrO4 (0.0025 M; 0.005 M) solutions containing 0.5 to 150 ppm of inactive or radioactive S= the potential shift was comparatively towards the noble direction. In Na2CrO4 (0.0025 M; 0.005 M) solutions containing 0.5 to 150 ppm of radioactive S= in Na2S, S pick‐up increased linearly with the increase in concentration of S= and the effect of increase in concentration of Na2CrO4 from 0.0025 M to 0.005 M did not show any appreciable increase in S pick‐up. Autoradiographs of the specimens immersed in the above solutions showed the presence of adsorbed S= on the mild steel surface and the linear increase in S pick‐up with the increase in concentration of S= in radioactive Na2S was observed. Mode of Cr pick‐up on mild steel in Na2CrO4 (0.0025 M, 0.00125 M) solutions was also studied for comparison purposes.

Right to Information (RTI) is a formidable tool in the hands of responsible citizens to fight corruption and ensure transparency and accountability within a participatory democracy. The RTI Act was promulgated in India in October 2005, and has fundamentally changed the power equation between the government and citizens. T.his chapter examines the contribution of the Act, in particular playing a significant role by providing information necessary to combat corruption in India. It is also noted, however, that RTI is not an unmixed-blessing as it is seen how costly it has been for zealous investigative journalists.

India has recently entered mandatory corporate social responsibility (CSR) spend era. It is important to unravel the pressures of CSR implementation in the Indian context to understand how a better fit between business strategy and CSR spend can be achieved. This study aims to validate a model that integrates pressures, CSR implementation and financial performance through reputation within the institutional theory framework.

It is based on a questionnaire survey of 162 top-level and middle-level CSR managers in India and semi-structured interviews with eight top-level executives.

The study concludes that local community, government, peers and media are important institutional pressures of CSR implementation in India. Reputation partially mediates the relationship between CSR implementation and financial performance.

The study findings can help managers to know which stakeholders (government, media, peers and local community) are exerting statistically significant institutional pressures and how CSR initiatives be designed to cater to their requirements. Though CSR spend is mandatory in India, a strategic orientation towards it would enable the firms to derive value for the stakeholders associated with the business.

Relationship between pressures of CSR and CSR implementation has not yet been explored in the Indian context. Such a relationship tells us why is CSR taken up and influence of which of the pressure groups is considered important while implementing CSR. The study will help to understand the relationship between CSR–reputation–financial performance as perceived by Indian managers and to assess whether they perceive corporate reputation building as one of the most important outcomes of CSR.

Background: Insurance was discovered many centuries before Christ (BC). In the second and third millennia BC, Chinese and Babylonian traders traded risks. Insurance is now the backbone of the economy, but penetration is low in developing countries. Big data, internet of things (IoT), and InsurTech have recently ushered in the fourth industrial revolution in insurance.

Objective: This study examines the Indian challenges and solutions of using Big Data Analytics (BDA).

methodology: A SLR was used to extract themes/variables related to challenges and solutions in adopting BDA in the Indian insurance sector. Google Scholar was searched for relevant literature using keywords. Inclusion and exclusion criteria were used to filter the studies.

Findings: This study identified several barriers to BDA adoption in the Indian insurance industry. Policymakers could use the suggestions to improve insurance service delivery.

Practical implication: Insurers can understand the challenges, and accordingly, they can adopt the proposed solution in this study to enhance the insurance penetration in India.

Wide differences in the focus and form of corporate social responsibility (CSR) exist among countries due to the different institutional embeddedness of CSR practices. The purpose of this paper is to seek to explain them within the framework provided by institutional theory by identifying important pressures driving CSR practices. Further, it intends to extend theory by proposing a conceptual model that relates institutional pressures, CSR practices, reputation and financial performance of corporates in a developing country like India.

Drawing upon the extant literature on the constructs, the paper describes their evolution through decades and weaves relationship between them. Institutional theory provides the framework to develop hypotheses.

The model has its roots in Scott’s institutional theory – linking regulative, normative and cognitive pressures to CSR practices. Reputation mediates the relationship between CSR and financial performance.

The conceptual model can serve as a foundation for subsequent empirical research. An understanding of relationship between constructs in the model will help corporates to strategize CSR initiatives. At the organisational level, insight into managerial perceptions of CSR practices will help to identify the need for training, if there is a gap between what organisation intends and what managers perceive.

The authors have proposed for the first time an integrative model that will help to understand the antecedents as well as consequences of CSR practices in a developing country within a theoretical framework.

Importance of corporate social responsibility (CSR) in marketing domain is increasing immensely. The effect of CSR perception on the purchase intention differs on the basis of mediators and contexts. The objective of this study is to examine the consumer behaviour of young consumers. For this, impact of CSR perception on purchase intention, satisfaction and price fairness of Generation Z is studied.

Preliminary data analysis is run to check normality, skewness and common method bias. PLS-SEM is deployed to examine the relationships amongst the research variables. Sequential mediation through PLS bootstrapping helped in exploring new and exciting research results which are supported with literature.

The CSR perception of Generation Z does not have a direct effect on their purchase intention. Interestingly, satisfaction and price fairness fully mediate the relationship between CSR perception and purchase intentions separately, i.e. CSR perception of Generation Z influences purchase intention only through satisfaction and price fairness. Furthermore, satisfaction and price fairness are also found to sequentially mediate the relationship between CSR perception and purchase intentions.

The research will aid not only the fast-food industry but the industries that are looking to focus on what Generation Z consumers expect in emerging markets including India. Understanding consumer expectations out of CSR initiatives will help them to incorporate social considerations into their marketing strategies and increase their profitability. Generation Z is regarded as the most challenging consumer demographic to market due to their proclivity for conducting extensive research and comparison shopping before making a purchase decision. As a result, the companies that want to use CSR as a strategy may find it advantageous to investigate how marketing of their CSR initiatives will lead to competitive edge and influence purchase decisions of this generational cohort.

This study adds to the academic literature by developing and evaluating a research model for consumer responses of a very important generation cohort to CSR in an emerging economy setting. CSR activities alone may not be enough to improve purchase intention of Generation Z adults. Sequential mediation for Generation Z adults' relationship between CSR and price fairness flows through satisfaction and finally to purchase intention is interesting because it clearly establishes a link amongst belief, attitude and actions of the target audience under study in a meaningful way within the framework given by cognitive consistency theory.

The extensive increase in power demand has challenged the ability of power systems to deal with small-signal oscillations such as inter-area oscillations, which occur under unseen operating conditions. A wide-area measurement system with a phasor measurement unit (PMU) in the power network enhances the observability of the power grid under a wide range of operating conditions. This paper aims to propose a wide-area power system stabilizer (WAPSS) based on Gaussian quantum particle swarm optimization (GQPSO) using the wide-area signals from a PMU to handle the inter-area oscillations in the system with a higher degree of controllability.

In the design of the wide-area stabilizer, a dead band is introduced to mitigate the influence of ambient signal frequency fluctuations. The location and the input signal of the wide-area stabilizer are selected using the participation factor and controllability index calculations. An improved particle swarm optimization (PSO) technique, namely, GQPSO, is used to optimize the variables of the WAPSS to move the unstable inter-area modes to a stable region in the s-plane, thereby improving the overall system stability.

The proposed GQPSO-based WAPSS is compared with the PSO-based WAPSS, genetic algorithm-based WAPSS and power system stabilizer. Eigenvalue analysis, time-domain simulation responses and performance index analysis are used to assess performance. The various evaluation techniques show that GQPSO WAPSS has a consistently good performance, with a higher damping ratio, faster convergence with fewer oscillations and a minimum error in the performance index analysis, indicating a more stable system with effective oscillation damping.

This paper proposes an optimally tuned design for the WAPSS with a wide-area input along with a dead-band structure for damping the inter-area oscillations. Tie line power is used as the input to the WAPSS and optimal tuning of the WAPSS is performed using an improved PSO algorithm, known as Gaussian quantum PSO.

In this article, the authors consider the following nonlinear singular boundary value problem (SBVP) known as Lane–Emden equations, −u″(t)-(α/t) u′(t) = g(t, u), 0 < t < 1 where α ≥ 1 subject to two-point and three-point boundary conditions. The authors propose to develop a novel method to solve the class of Lane–Emden equations.

The authors improve the modified variation iteration method (VIM) proposed in [JAAC, 9(4) 1242–1260 (2019)], which greatly accelerates the convergence and reduces the computational task.

The findings revealed that either exact or highly accurate approximate solutions of Lane–Emden equations can be computed with the proposed method.

Novel modification is made in the VIM that provides either exact or highly accurate approximate solutions of Lane-Emden equations, which does not exist in the literature.

Predicting commodity futures trading volumes represents an important matter to policymakers and a wide spectrum of market participants. The purpose of this study is to concentrate on the energy sector and explore the trading volume prediction issue for the thermal coal futures traded in Zhengzhou Commodity Exchange in China with daily data spanning January 2016–December 2020.

The nonlinear autoregressive neural network is adopted for this purpose and prediction performance is examined based upon a variety of settings over algorithms for model estimations, numbers of hidden neurons and delays and ratios for splitting the trading volume series into training, validation and testing phases.

A relatively simple model setting is arrived at that leads to predictions of good accuracy and stabilities and maintains small prediction errors up to the 99.273th quantile of the observed trading volume.

The results could, on one hand, serve as standalone technical trading volume predictions. They could, on the other hand, be combined with different (fundamental) prediction results for forming perspectives of trading trends and carrying out policy analysis.