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This study aims to obtain earthquake responses of linear-elastic multi-span arch-frames by using exact curved beam formulations. For this purpose, the dynamic stiffness method (DSM) which uses exact mode shapes is applied to a three-span arch-frame considering axial extensibility, shear deformation and rotational inertia for both columns and curved beams. Using exact free vibration properties obtained from the DSM approach, the arch-frame model is simplified into an equivalent single degree of freedom (SDOF) system to perform earthquake response analysis.

The dynamic stiffness formulations of curved beams for free vibrations are validated by using the experimental data in the literature. The free vibrations of the arch-frame model are investigated for various span lengths, opening angle and column dimensions to observe their effects on the dynamic behaviour. The calculated natural frequencies via the DSM are presented in comparison with the results of the finite element method (FEM). The mode shapes are presented. The earthquake responses are calculated from the modal equation by using Runge-Kutta algorithm.

The displacement, base shear, acceleration and internal force time-histories that are obtained from the proposed approach are compared to the results of the finite element approach where a very good agreement is observed. For various span length, opening angle and column dimension values, the displacement and base shear time-histories of the arch-frame are presented. The results show that the proposed approach can be used as an effective tool to calculate earthquake responses of frame structures having curved beam elements.

The earthquake response of arch-frames consisting of curved beams and straight columns using exact formulations is obtained for the first time according to the best of the author’s knowledge. The DSM, which uses exact mode shapes and provides accurate free vibration analysis results considering each structural members as one element, is applied. The complicated structural system is simplified into an equivalent SDOF system using exact mode shapes obtained from the DSM and earthquake responses are calculated by solving the modal equation. The proposed approach is an important alternative to classical FEM for earthquake response analysis of frame structures having curved members.

The purpose of this study is data generated from any social networking sites may provide some hidden knowledge on a particular domain. Based on this concept the previous paper had proved that social connectivity enhancement takes place through triadic closure and embeddedness in terms of social network graph-theoretic approach. Further, the work was justified by genetic algorithm (GA) where observation showed how interdisciplinary work can occur because of crossover, and therefore, different groups of researchers could be identified. Further enhancement of the work has been focused on in this paper.

In continuation with the previous work, this paper detects other possible fields related to “high graded researchers” who can share the information with the other group of researchers (“imminent high graded” and “new researchers”) using particle swarm optimization (PSO) technique.

While exploitation was done using GA in the previous work, exploration is done in the current work based on PSO using the same grade score value to the objective function. Both the velocity and direction of high graded researchers in this extended work could be derived, which was not possible using GA.

This could help the next two levels of researchers (“imminent high graded researchers” and “new researchers”) in expanding their research fields in line with the fields of high graded researchers.

This study aims to examine the technical efficiency of the chemical-free farming system in India using a hybrid combination of data envelopment analysis (DEA) and machine learning (ML) approaches.

The study used a two-stage approach. In the first stage, the efficiency scores of decision-making units’ efficiency (DMUs) are obtained using an input-oriented DEA model under the assumption of a variable return to scale. Based on these scores, the DMUs are classified into efficient and inefficient categories. The 2nd stage of analysis involves the identification of the most important predictors of efficiency using a random forest model and a generalized logistic regression model.

The results show that by using their resources efficiently, growers can reduce their inputs by 34 percent without affecting the output. Orchard's size, the proportion of land, grower's age, orchard's age and family labor are the most important determinants of efficiency. Besides, growers' main occupation and footfall of intermediaries at the farm gate also demonstrate significant influence on efficiency.

The study used only one output and a limited set of input variables. Incorporating additional variables or dimensions like fertility of the land, climatic conditions, altitude of the land, output quality (size/taste/appearance) and per acre profitability could yield more robust results. Although pineapple is cultivated in all eight northeastern states, the data for the study has been collected from only two states. The production and marketing practices followed by the growers in the remaining six northeastern states and other parts of the country might be different. As the growers do not maintain farm records, their data might suffer from selective retrieval bias.

Given the rising demand for organic food, improving the efficiency of chemical-free growers will be a win-win situation for both growers and consumers. The results will aid policymakers in bringing necessary interventions to make chemical-free farming more remunerative for the growers. The business managers can act as a bridge to connect these remote growers with the market by sharing customer feedback and global best practices.

Although many developments have happened to the DEA technique, the present study used a traditional form of DEA. Therefore, future research should combine ML techniques with more advanced versions like bootstrap and fuzzy DEA. Upcoming research should include more input and output variables to predict the efficiency of the chemical-free farming system. For instance, environmental variables, like climatic conditions, degree of competition, government support and consumers' attitude towards chemical-free food, can be examined along with farm and grower-specific variables. Future studies should also incorporate chemical-free growers from a wider geographic area. Lastly, future studies can also undertake a longitudinal estimation of efficiency and its determinants for the chemical-free farming system.

No prior study has used a hybrid framework to examine the performance of a chemical-free farming system.

From the perspective of cause and effect, the operational processes of property insurance companies can be considered as historical events. The purpose of this study is to measure the operating efficiency of China's property insurance industry, explore the determinants that affect technical efficiency and outline the path to achieving high-quality development.

We chose 44 Chinese property insurance companies as research objects. The data were obtained from the Chinese Insurance Yearbook and China Statistical Yearbook 2015–2017. First, the data envelopment analysis (DEA) method was used to calculate the technical efficiency of property insurance companies. Then, Tobit regression and quantile regression were adopted to explore the influencing factors of technical efficiency. Finally, the fuzzy-set qualitative comparative analysis (fsQCA) method was employed to summarize the path to improving the operating efficiency of property insurance companies.

The empirical results in the first stage suggested that the operation efficiency of China's property insurance industry was technically inefficient, and the scale efficiency was relatively better than the pure technical efficiency. In the second stage, we observed that the drivers for firm size, reinsurance rate, claim ratio and equity restriction were important determinants of an insurance firm's efficiency.

We also put forward four applicable, targeted and proven ways to improve the technical efficiency of property insurance companies. These configurations are verified by cases of existing property insurance companies, which can provide practical references for the insurance industry.

Our research enriches the insurance literature and efficiency methods, particularly regarding the specific paths of improving the technical efficiency. The relationship between elements and results is analyzed from a systematic perspective, and the research results are not only more consistent with what logic might imply but also more instructive for the improvement of reality.

The purpose of this paper is to present a design sensitivity analysis continuum formulation for the cross-section properties of thin-walled laminated composite beams. These properties are expressed as integrals based on the cross-section geometry, on the warping functions for torsion, on shear bending and shear warping, and on the individual stiffness of the laminates constituting the cross-section.

In order to determine its properties, the cross-section geometry is modeled by quadratic isoparametric finite elements. For design sensitivity calculations, the cross-section is modeled throughout design elements to which the element sensitivity equations correspond. Geometrically, the design elements may coincide with the laminates that constitute the cross-section.

The developed formulation is based on the concept of adjoint system, which suffers a specific adjoint warping for each of the properties depending on warping. The lamina orientation and the laminate thickness are selected as design variables.

The developed formulation can be applied in a unified way to open, closed or hybrid cross-sections.

The present study tries to explore the various fund attributes that influence the mutual fund performance. Further, study examined the effect of mutual fund attributes namely, Net Asset Value (NAV), Portfolio turnover ratio (PTR), fund size (AUM), expense ratio (ExpR) and fund age (Age) on mutual fund's performance using gross return and risk-adjusted performance measures.

The study evaluated balanced panel data (short panel) comprising 81 Indian equity mutual fund schemes for the period of 2013–2019. The study estimated relationship between fund attributes (Net asset value, Portfolio turnover ratio, Fund age, fund size and Expense ratio) and fund performance (using gross return and risk-adjusted performance measures), through panel data regression using fixed-effects model as suggested by Hausman specification test on transformed data (due to high multicollinearity), with cluster-robust estimators due to the presence of heteroskedasticity in the model.

The findings of the study suggested that using gross return as fund performance measure, PTR, NAV, AUM, Age exhibit significant relationship with the fund performance whereas using risk-adjusted performance measures (Treynor ratio and Jensen alpha) NAV and ExpR significantly influences the fund performance. Identification of the significant relationship between fund characteristics and fund performance offers valuable insights to the investors and fund managers for rationally managing their portfolio with the ultimate objective of the wealth maximization.

The study considered only 81 equity mutual fund schemes. Some of the data were not available at the time of the study due to the policy of the company. The present study contributes significantly in examining the expected association between fund attributes and fund performance in the context of Indian mutual fund industry where this relationship were explored less.

The findings of the present study will help the investors to take the rational investment decision with the ultimate objective of maximum return with minimal risk. The findings also offer significant germane to the stakeholders in making rational decision-making process.

There is dearth of study concerning the relationship between mutual fund characteristics and fund performance with respect to Indian mutual fund industry. Therefore, study provides valuable insights to the area of the portfolio selection and management with respect to Indian mutual funds.

The purpose of this article is to evaluate revenue efficiency performance of life insurance companies in India. The study also compares if private or public insurance sector is more “revenue efficient”. Furthermore, the study determines the nature of return to scale (RTS) and identifies the leaders and laggards amongst insurance companies operating in India.

Revenue efficiency is calculated by employing data envelopment analysis – a non-parametric approach, on a data set of 24 insurance companies over the period 2013–2014 to 2017–2018.

The empirical results suggest that life insurance companies in India could generate only 34.4% of revenue, which is very less than what these are expected to generate from the same inputs. Majority of life insurance companies operating in India are operating at decreasing return to scale (DRS). There is a reduction in leaders and the highest proportion of companies is falling in the category of laggards.

As per the best knowledge of researchers, no empirical work has been carried out with respect to measuring the revenue efficiency of Indian insurance companies. The current study appropriately fills the gap by not only calculating the revenue efficiency scores of insurance companies in India but also provides insights into the causes of revenue inefficiencies. It also gives implications for efficient and effective management of insurance companies.

Recent technological advancements, often linked to Industry 4.0, require organizations to be more agile and innovative. Blockchain technology (BT) holds immense potential in driving organizations to achieve efficiency and transparency in supply chains. However, there exist some insurmountable challenges associated with the adoption of BT in organizational supply chains (SC). This paper attempts to categorically identify and systematize the most influential challenges in the implementation of BT in SC.

This study resorts to an extensive literature review and consultations with experts in the field of supply chain management (SCM), information technology and academia to identify, categorize and prioritize the major challenges using VlseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and Combined Compromise Solution method (CoCoSo).

The top three classes of challenges revealed in this study are privacy challenges (PC), infrastructure challenges (IC) and transparency challenges (TC). Maintaining a balance between data openness and secrecy and rectification of incorrect/erroneous input are the top two challenges in the PC category, integration of BT with sustainable practices and ensuring legitimacy are the top two challenges in the IC category, and proper and correct information sharing in organizations was the top most challenge in the TC category.

Future scholars and industry professionals will be guided by the importance of the challenges identified in this study to develop an economical and logical approach for integrating BT to increase the efficiency and outcome of supply chains across several industrial sectors.

Inadequacies in several micronutrients in complementary foods, notably iron, zinc, calcium, vitamin A, vitamin B6 and riboflavin have been reported. Moringa oleifera leaf powder (MLP), prepared from dried moringa leaves is nutrient-rich and has been explored for the treatment of micronutrient deficiencies among children in developing countries. This increasing interest in the use of moringa oleifera leaves to improve complementary foods notwithstanding, the unique sensory characteristics of the leaf powder potentially holds implications for the acceptability of local diets that are fortified with it. The purpose of this paper is to investigate the levels of MLP fortification that are most acceptable for feeding infants and young children.

The authors performed a review of the literature, with the aim of investigating the sensory attributes and acceptable levels of fortification of complementary food blends fortified with different levels of MLP.

The minimum amount of MLP to be added to a complementary food blend to observe significant improvements in its nutritional value was estimated to be about 10 per cent. However, at this 10 per cent fortification level also, sensory attributes of the products begin to become less desirable.

For the success of nutrition interventions that involve the use of MLP to improve the nutritional quality of complementary foods, there is a need to consider the acceptability of the sensory attributes of the formulated blends in the target group. Safety of MLP as an ingredient in infant foods must also be investigated.

The authors of this paper make recommendations for the use of MLP to fortify complementary foods to ensure its success as a food fortificant in nutrition interventions. The researchers are not aware of any published study that focuses on this subject.

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.