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Several studies have examined the relationship between spin-off announcements and stock performance. However, a comparison of the announcement effect of different schemes of spin-offs remains relatively underexplored in the literature. This study aims to find the differential impact of pure scheme and composite schemes of spin-offs on parent company stock performance. A pure scheme includes only the separation of business into independent companies, while a composite scheme includes a simultaneous merger of one of the companies with another company along with separation.

A total of 109 pure and 51 composite spin-off announcements made by Indian listed companies from 2010 to 2023 are examined using event study methodology. The cross-sectional t-test is used to measure the significance of abnormal returns. The t-test for two sample means (right-tailed) is incorporated to test the significance of variations in the stock returns of pure and composite schemes of spin-off announcements. Cross-sectional regression is also done to evaluate the impact of the type of scheme on the spin-off return.

The study found a cumulative average abnormal return of −1.06% for the pure spin-off and 8.27% for the composite spin-off over a 41-day event window. The univariate analysis revealed that the composite scheme generates a significantly higher cumulative average abnormal return than the pure scheme. Regression analysis also confirmed that the composite scheme significantly positively impacts the stock return. It can be concluded that investors favour the composite scheme, expecting that it will deliver a better strategic fit and generate synergy.

This paper makes a valuable contribution to the existing literature on corporate spin-offs. The study by analysing and comparing how the spin-off and merger combination differently affects the stock performance, helps the investor who wants to capitalize on the market imperfections and the managers to make complex business decisions.

The purpose of this paper is to study the anodising process of a portable amplifier production process to identify and eliminate the sources of variations, in order to improve the process productivity.

The study employs the define-measure-analyse-improve-control (DMAIC) Six Sigma methodology. Within the DMAIC framework various tools of quality management such as SIPOC analysis, cause and effect diagram, current reality tree, etc., are used in different stages.

High rejection rate was found to be the main problem leading to lower productivity of the process. Four types of defects were identified as main cause of rejections in the baseline process. Pareto analysis resulted in detection of the top defects, which were then analysed in details to find the root cause of the problem. Further study resulted in finding improvement measures that were discussed with the management before implementation. The process is sampled again to check the improvements, and control measures were established.

The study provides a framework for implementation of DMAIC Six Sigma methodology for a manufacturing firm. The results presented are based on the data collected from the shop floor. Results and findings of the study were implemented for quality improvement of the process.

The study is based on an original research conducted with the objective of quality improvement in the anodising process of the production process. Besides presenting an approach to DMAIC Six Sigma methodology, an application of the current reality tree tool for root cause analysis is presented, a tool used limitedly in the Six Sigma studies. The tool finds its uniqueness in its ability to address problems relating multiple factors than isolated factors.

The purpose of this paper is to evaluate the suitability of cloud computing for small and medium-sized enterprises (SMEs) in India.

Literature review is used to identify benefits, challenges, and factors concerning usage and adoption of cloud computing by SMEs. A conceptual framework was developed based on the existing theoretical models and factors identified from the literature. A survey based on questionnaire method was followed to collect data from 121 manufacturing SMEs in India. The conceptual framework was refined by using factor analysis, and multiple regression analysis was used to test the hypotheses.

Major benefits of cloud computing for SMEs include cost advantage, easy deployment process, easier access to latest information and communication technologies, automatic updates and upgrades, scalability, flexibility, and improved disaster recovery and back-up capabilities. The concern area includes perceived loss of control, vendor lock-in, security issues, reliability and availability issues, and internet connectivity and speed. The factors that are found significant include perceived benefits, top management support, competitive pressure, and perceived concerns. The model explained 73 percent of cloud computing adoption.

The study is expected to make significant contribution toward body of knowledge pertaining to information technology adoption in SMEs.

The study is expected to provide SMEs an insight into real benefits and challenges associated with adopting cloud computing. The model can help SMEs in evaluating their readiness for adopting cloud computing and can ensure successful outcome of cloud computing adoption in SMEs. Providers are also going to be benefited through their enhanced understanding of SMEs’ requirements.

The proposed framework incorporates all the relevant factors including perceived benefits, perceived concerns, and other organizational and environmental factors to improve model’s predictive power.

The purpose of this paper is to examine various technological innovation influencers (TIIs) in small manufacturing firms. It introduces a study framework of technological innovation and evaluates the relevance of four TIIs to building and sustaining the competitiveness of Indian firms.

This research is based on an in-depth survey of 135 firms located in India’s Northern region. Multiple regression analysis was employed to examine the correlation between TIIs and manufacturing firm performance (MFP) for these firms.

The findings verify that entrepreneurial capability, technology infrastructure capability and government initiatives are the most important TIIs for small firms. The findings are also validated by using statistical t-test and canonical correlation analysis.

This study uses a single informant as the source of information on each firm. The study is limited to small-scale firms in the Northern region of India. Also, the study has been conducted excluding the service sector.

Recent studies have advocated various TIIs and discussed their impact on MFP. This paper examines the determinants of technological innovation in small manufacturing firms. It introduces a study framework of technological innovation and examines the relevance of four TIIs to building and sustaining the competitiveness of Indian firms.

This paper aims to explore the factors for self-help groups (SHGs) women empowerment in the state of Uttar Pradesh using the primary data.

The primary data have been collected by a household survey in the four districts of Uttar Pradesh. Factor analysis is used to estimate the odd of improving women empowerment after participating in SHG.

Factor analysis extracted four factors which were economic development, improvement in family matters, decision to use public amenities and political empowerment. Also, analysis of variance and t-test was used employing SPSS. The results, therefore, show that education has a significant impact on all the aspects of SHGs people.

The findings of the study can help policymakers to adopt appropriate policies that integrate empowerment in development projects with women.

The results of this research could encourage more women to participate in SHG activities and development projects.

This research provides the most updated data from a primary survey in the state of Uttar Pradesh.

The purpose of this paper is to understand the role of entrepreneurial intention in promoting women entrepreneurship in Indian micro, small and medium enterprises (MSMEs). This study seeks to clarify the construct of entrepreneurial intention and then reports the validation of the entrepreneurial intention instrument.

An instrument has been designed and administered on a sample of 103 respondents across India from women entrepreneurs to understand the entrepreneurial intention by using cluster and snowball sampling. The data has been streamlined and then analyzed using descriptive analysis for validity and reliability checks.

This research was aimed to determine the constructs of entrepreneurial intention. Through data analysis, it has been observed that the reliability coefficients reveal the adequacy of the sample. The Cronbach’s alpha values for all the items in the instrument were found to be greater than or equal to 0.6. Strong correlations were also found between direct and indirect measures of entrepreneurial intention and hence confirmed that all the measures in the instrument were well constructed. Analysis has also explained the relationship between various constructs of entrepreneurial intention by using Pearson’s correlation coefficients. Strong and positive values of correlation explain the existence of the convergent and discriminant validity of the instrument.

The research results obtained from the analysis of reliability and validity tests not only provides the establishment of the relationship among the various constructs but also suggests that the model provides a promising potential to measure entrepreneurial intention. This study will contribute to new knowledge of the conditions of women entrepreneurship from different perspectives by developing and validating an analytic model for promoting the women entrepreneurship in MSMEs of India.

From a government perspective, this model will help in designing training programmes for promoting women entrepreneurship in India. The obtained result also brings significant implications for practice as well as raises a broad future direction for other researchers

Extended SCCT model has recently suggested an inclusive framework of factors affecting the entrepreneurial intention, there is not much attempt made in research using this theory as background for predicting intention in the context of women entrepreneurship. This paper attempts to fill this gap by formulating a conceptual model for measuring entrepreneurial intention among women entrepreneurs by integrating and adapting the constructs of extended social cognitive career theory model and entrepreneurial potential model.

This paper aims to discuss a new form of the Adomian decomposition technique for the numerical treatment of Bratu’s type one-dimensional boundary value problems (BVPs). Moreover, the author also addresses convergence and error analysis for the completeness of the proposed technique.

First, the author discusses the standard Adomian decomposition method and an algorithm based on Duan’s corollary and Rach’s rule for the fast calculation of the Adomian polynomials. Then, a new form of the Adomian decomposition technique is present for the numerical simulation of Bratu’s BVPs.

The reliability and validity of the proposed technique are examined by calculating the absolute errors of Bratu’s problem for some different values of Bratu parameter λ. Numerical simulation demonstrates that the proposed technique yields higher accuracy than the Bessel collocation and other known methods.

Unlike the other methods, the proposed technique does not need linearization, discretization or perturbation to handle the non-linear problems. So, the results obtained by the present technique are more physically realistic.

This study explores the immobilisation of enzymes within porous catalysts of various geometries, including spheres, cylinders and flat pellets. The objective is to understand the irreversible Michaelis-Menten kinetic process within immobilised enzymes through advanced mathematical modelling.

Mathematical models were developed based on reaction-diffusion equations incorporating nonlinear variables associated with Michaelis-Menten kinetics. This research introduces fractional derivatives to investigate enzyme reaction kinetics, addressing a significant gap in the existing literature. A novel approximation method, based on the independent polynomials of the complete bipartite graph, is employed to explore solutions for substrate concentration and effectiveness factor across a spectrum of parameter values. The analytical solutions generated through the bipartite polynomial approximation method (BPAM) are rigorously tested against established methods, including the Bernoulli wavelet method (BWM), Taylor series method (TSM), Adomian decomposition method (ADM) and fourth-order Runge-Kutta method (RKM).

The study identifies two main findings. Firstly, the behaviour of dimensionless substrate concentration with distance is analysed for planar, cylindrical and spherical catalysts using both integer and fractional order Michaelis-Menten modelling. Secondly, the research investigates the variability of the dimensionless effectiveness factor with the Thiele modulus.

The study primarily focuses on mathematical modelling and theoretical analysis, with limited experimental validation. Future research should involve more extensive experimental verification to corroborate the findings. Additionally, the study assumes ideal conditions and uniform catalyst properties, which may not fully reflect real-world complexities. Incorporating factors such as mass transfer limitations, non-uniform catalyst structures and enzyme deactivation kinetics could enhance the model’s accuracy and broaden its applicability. Furthermore, extending the analysis to include multi-enzyme systems and complex reaction networks would provide a more comprehensive understanding of biocatalytic processes.

The validated bipartite polynomial approximation method presents a practical tool for optimizing enzyme reactor design and operation in industrial settings. By accurately predicting substrate concentration and effectiveness factor, this approach enables efficient utilization of immobilised enzymes within porous catalysts. Implementation of these findings can lead to enhanced process efficiency, reduced operating costs and improved product yields in various biocatalytic applications such as pharmaceuticals, food processing and biofuel production. Additionally, this research fosters innovation in enzyme immobilisation techniques, offering practical insights for engineers and researchers striving to develop sustainable and economically viable bioprocesses.

The advancement of enzyme immobilisation techniques holds promise for addressing societal challenges such as sustainable production, environmental protection and healthcare. By enabling more efficient biocatalytic processes, this research contributes to reducing industrial waste, minimizing energy consumption and enhancing access to pharmaceuticals and bio-based products. Moreover, the development of eco-friendly manufacturing practices through biocatalysis aligns with global efforts towards sustainability and mitigating climate change. The widespread adoption of these technologies can foster a more environmentally conscious society while stimulating economic growth and innovation in biotechnology and related industries.

This study offers a pioneering approximation method using the independent polynomials of the complete bipartite graph to investigate enzyme reaction kinetics. The comprehensive validation of this method through comparison with established solution techniques ensures its reliability and accuracy. The findings hold promise for advancing the field of biocatalysts and provide valuable insights for designing efficient enzyme reactors.

The numerical methods are of great importance for approximating the solutions of a system of nonlinear singular ordinary differential equations. In this paper, the authors present the biorthogonal flatlet multiwavelet collocation method (BFMCM) as a numerical scheme for a class of system of Lane–Emden equations with initial or boundary or four-point boundary conditions.

The approach is involved in combining the biorthogonal flatlet multiwavelet (BFM) with the collocation method. The authors investigate the properties and procedure of the BFMCM for first time on this class of equations. By using the BFM and the collocation points, the method is constructed and it transforms the nonlinear differential equations problem into a system of nonlinear algebraic equations. The unknown coefficients of the assuming solution are determined by solving the obtained system. Additionally, convergence analysis and numerical stability of the suggested method are provided.

According to the attained results, the proposed BFMCM has more accurate results in comparison with results of other methods. The maximum absolute errors are calculated by using the BFMCM for comparison purposes provided.

The key desirable properties of BFMCM are its efficiency, simple applicability and minimizes errors. Therefore, the proposed method can be used to solve nonlinear problems or problems with singular points.

The numerical solution of third-order boundary value problems (BVPs) has a great importance because of their applications in fluid dynamics, aerodynamics, astrophysics, nuclear reactions, rocket science etc. The purpose of this paper is to develop two computational methods based on Hermite wavelet and Bernoulli wavelet for the solution of third-order initial/BVPs.

Because of the presence of singularity and the strong nonlinear nature, most of third-order BVPs do not occupy exact solution. Therefore, numerical techniques play an important role for the solution of such type of third-order BVPs. The proposed methods convert third-order BVPs into a system of algebraic equations, and on solving them, approximate solution is obtained. Finally, the numerical simulation has been done to validate the reliability and accuracy of developed methods.

This paper discussed the solution of linear, nonlinear, nonlinear singular (Emden–Fowler type) and self-adjoint singularly perturbed singular (generalized Emden–Fowler type) third-order BVPs using wavelets. A comparison of the results of proposed methods with the results of existing methods has been given. The proposed methods give the accuracy up to 19 decimal places as the resolution level is increased.

This paper is one of the first in the literature that investigates the solution of third-order Emden–Fowler-type equations using Bernoulli and Hermite wavelets. This paper also discusses the error bounds of the proposed methods for the stability of approximate solutions.