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Investigate the distinctive link between a balanced scorecard and organizational performance in ITand non-IT sectors
Purpose: The purpose of this research is to examine how the implementation of a balanced scorecard (BSC) affects business outcomes in both information technology (IT) and non-IT sectors. Design/methodology/approach: Partial least squares structural equation modeling (PLS-SEM) was used to test the hypothesis. A random sample was used to collect 170 responses from the IT companies and 166 from non-IT companies by using the questionnaire method. The questionnaire was distributed to the top- and middle-level managers in Bangalore city, and we used SmartPLS software to explore the relationship between our research constructs. Findings: The results of this study indicate that a BSC has a significant and positive impact on organizational performance in IT and non-IT sectors. The main distinction in this study is that all BSC perspectives [learning and growth perspective, internal business process (IBP) perspective, customer perspective (CP) and financial perspective (FP)] have a significant, direct and indirect impact on IT companies. On the other hand, solely three BSC perspectives (IBP perspective, CP and FP) have a significant impact on non-IT companies, while learning and growth perspective has an insignificant impact on the FP. Originality/value: This study provides a critical theoretical and practical contribution of a BSC on business performance in IT and non-IT industries. 2024, Emerald Publishing Limited. -
On ?(k)-colouring of Some Wheel Related Graphs
The question on how to colour a graph G when the number of available colours to colour G is less than that of the chromatic number ?(G), such that the resulting colouring gives a minimum number of edges whose end vertices have the same colour, has been a study of great interest. Such an edge whose end vertices receives the same colour is called a bad edge. In this paper, we use the concept of ?(k)-colouring, where 1 ? k ? ?(G) ? 1, which is a near proper colouring that permits a single colour class to have adjacency between the vertices in it and restricts every other colour class to be an independent set, to find the minimum number of bad edges obtained from the same for some wheel related graphs. The minimum number of bad edges obtained from ?(k)-colouring of any graph G is denoted by bk(G). 2024 the Author(s), licensee Combinatorial Press. -
Modelling Climate, COVID-19, and Reliability Data: A New Continuous Lifetime Model under Different Methods of Estimation
In this article, a new continuous probability distribution called Arvind distribution is developed and studied. The proposed distribution has only one parameter but it exhibits a wide variety of shapes for density and hazard rate functions. A number of important distributional properties including mode, quantile function, moments, skewness, kurtosis, mean deviation, probability-weighted moments, stress-strength reliability, order statistics, reliability and hazard rate functions, Bonferroni Lorenz and Zenga curves, conditional moments, mean residual and mean past life functions, and stochastic ordering of the Arvind distribution are derived. For point estimation of the parameter of the proposed distribution, six estimation procedures including maximum likelihood, maximum product spacings, least squares, weighted least squares, Cram-von Mises, and Anderson-Darling estimators are used. The interval estimation of the unknown parameter has also been discussed using observed Fishers information. A vast simulation study has been conducted to examine the behaviour of different estimation procedures. Finally, the applicability of the proposed model is demonstrated by using three real-life datasets. The results of the real data analysis clearly announce that the Arvind distribution can be a better alternative to several existing models for modelling different types of data from various fields. 2024, Society of Statistics, Computer and Applications. All rights reserved. -
Multifunctional SnO?-Chitosan-D-carvone Nanocomposite: A Promising Antimicrobial, Anticancer, and Antioxidant Agent for Biomedical Applications
Nanocomposite made up of inorganic and biocompatible polymer have gained significant attention for biomedical applications due to their enhanced multifunctional properties, offering solutions to serious issues like antimicrobial resistance and cancer treatment. Nanocomposite composed of SnO?, chitosan and D-carvone (SnO2-Cs-Dcar) was prepared to ascertain its efficacy in application for antimicrobial, anticancer activities, and antioxidant effects. The synthesized nanocomposite was characterized by XRD, UV-Vis, FTIR, PL, SEM, TEM, and XPS techniques, confirming successful integration. XRD results confirmed the tetragonal rutile phase of SnO2. The band gap energy was calculated as 4.32eV for SnO2 nanoparticles and 3.11eV for SnO2-Cs-Dcar nanocomposite as observed from UV-Visible spectra. PL emission results showed that SnO2-Cs-Dcar nanocomposite exhibited green emission at 507nm corresponds to number oxygen vacancy site. SEM and TEM results showed that the SnO2-Cs-Dcar nanocomposite entities appear more compact, and the single SnO2 particles are less differentiated, possibly because they have been covered by chitosan and D-carvone. Antimicrobial activity against the pathogens Klebsiella pneumoniae, Candida albicans, Shigella dysenteriae, Bacillus subtilis, and Staphylococcus aureus demonstrated that SnO2-Cs-Dcar exhibited enhanced bacteriostatic effect when compared to bare SnO2. MTT assay on MOLT-4 cancer cells revealed that SnO2-Cs-Dcar nanocomposite exhibited enhanced anticancer activity upon compared to SnO? nanoparticles. The IC50 values were calculated as 13.6 for SnO2 and 12.1 for SnO2-Cs-Dcar nanocomposite. SnO?-Cs-Dcar nanocomposites exhibits high antioxidant activity evidenced by improved free radical scavenging action in comparison with a bare SnO?. Experimental result indicates that the SnO?-Cs-Dcar nanocomposites can be used as biocidal agent for antimicrobial and anticancer therapies. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2024. -
Effects of Yoga and Combined Yoga with Neuro-Linguistic Programming on Psychological Management in Mothers of Adolescents: A Randomized Controlled Trial
Adolescent parenting presents significant challenges for mothers, often leading to elevated levels of stress and anxiety that can adversely affect their well-being and parenting effectiveness. This study aims to evaluate the efficacy of yoga alone and in combination with Neuro-Linguistic Programming (NLP) in managing stress and anxiety among mothers of adolescent children. In this randomized controlled trial, 90 participants aged 35-55 years (mean age 44.564.58 years), each with at least one child aged 13-19 years, were randomly assigned to one of three groups: control, yoga, or yoga with NLP. Interventions were conducted over 12 weeks, with outcome measures assessed pre- and post-intervention by trained research assistants blinded to group allocation. The Depression, Anxiety, and Stress Scale (DASS-21), and Pittsburgh Sleep Quality Index (PSQI), were utilized to evaluate outcomes. Both intervention groups demonstrated significant reductions in depression, anxiety, and stress levels compared to the control group. The yoga with NLP group exhibited superior improvements across all primary outcomes, with statistically significant differences noted in depression (mean difference =7.1, p<0.001), anxiety (mean difference =5.1, p<0.001) and stress levels (mean difference =5.5, p<0.001). Additionally, sleep quality improved significantly in both intervention groups, with the yoga with NLP group showing greater benefits. This study provides evidence that yoga, particularly in combination with NLP, is an effective non-pharmacological approach for reducing stress and anxiety and improving sleep quality among mothers of adolescents. These findings support the integration of mind-body practices into mental health care, highlighting the potential synergistic benefits of combining physical and cognitive interventions. Future research should explore long-term effects and the mechanisms underlying these improvements. 2024 Montenegrin Sports Academy. All rights reserved. -
Carboplatin-loaded zeolitic imidazolate framework-8: Induction of antiproliferative activity and apoptosis in breast cancer cell
The challenge with breast cancer is its ongoing high prevalence and difficulties in early detection and access to effective care. A solution lies in creating tailored metalorganic frameworks to encapsulate anticancer drugs, enabling precise and targeted treatment with less adverse effects and improved effectiveness. Zeolitic imidazolate framework-8 (ZIF-8) and carboplatin (CP)-loaded ZIF-8 were synthesized and characterized using various analytical techniques. High Resolution-transmission electron microscopy of ZIF-8 and CP@ZIF-8 indicates that the particles had a spherical shape and were nanosized. The drug release rate of CP is 98% under an acidic medium (pH 5.5) because of the dissolution of ZIF-8 into its coordinating ions, whereas 35% in a physiological medium (pH 7.4) with the addition of CP, the high porosity, and pore diameter of ZIF-8 decrease from 1243 to 1041m2/g. Breast cancer MCF-7 cells were shown greater IC50 in CP@ZIF-8 (15.013.03g/mL) than free CP (34.984.25g/mL) in an in vitro cytotoxicity assessment. The cytotoxicity of the CP@ZIF-8 against MCF-7 cells was studied using the methylthiazolyldiphenyl-tetrazolium bromide method. The morphological changes were examined using fluorescent staining (acridine orangeethidium bromide and Hoechst 33258) methods. The comet assay assessed the DNA fragmentation (single-cell gel electrophoresis). The results from the study revealed that CP@ZIF-8 can be used in the treatment of breast cancer. 2024 International Union of Biochemistry and Molecular Biology, Inc. -
A Worldwide Test of the Predictive Validity of Ideal Partner Preference Matching
Ideal partner preferences (i.e., ratings of the desirability of attributes like attractiveness or intelligence) are the source of numerous foundational findings in the interdisciplinary literature on human mating. Recently, research on the predictive validity of ideal partner preference matching (i.e., Do people positively evaluate partners who match vs. mismatch their ideals?) has become mired in several problems. First, articles exhibit discrepant analytic and reporting practices. Second, different findings emerge across laboratories worldwide, perhaps because they sample different relationship contexts and/or populations. This registered reportpartnered with the Psychological Science Acceleratoruses a highly powered design (N = 10,358) across 43 countries and 22 languages to estimate preference-matching effect sizes. The most rigorous tests revealed significant preference-matching effects in the whole sample and for partnered and single participants separately. The corrected pattern metric that collapses across 35 traits revealed a zero-order effect of ? =.19 and an effect of ? =.11 when included alongside a normative preference-matching metric. Specific traits in the level metric (interaction) tests revealed very small (average ? =.04) effects. Effect sizes were similar for partnered participants who reported ideals before entering a relationship, and there was no consistent evidence that individual differences moderated any effects. Comparisons between stated and revealed preferences shed light on gender differences and similarities: For attractiveness, mens and (especially) womens stated preferences underestimated revealed preferences (i.e., they thought attractiveness was less important than it actually was). For earning potential, mens stated preferences underestimatedand womens stated preferences overestimatedrevealed preferences. Implications for the literature on human mating are discussed. 2024 American Psychological Association -
Is corporate reputation associated with voluntary cybersecurity risk reporting?
Purpose: This study investigated the effect of voluntary cybersecurity risk reporting (VCRR) on corporate reputation. By examining the association between VCRR and corporate reputation, this study aims to provide exploratory evidence of how cybersecurity risk is sensitive to a companys image and reputation. Design/methodology/approach: An automated content analysis of VCRR by 95 Bombay Stock Exchange-listed companies was undertaken using Python code. Signaling and legitimacy theories were adopted to interpret the findings, establishing whether VCRR was related to corporate reputation. Findings: The results confirm that VCRR improves the corporate reputation in the financial market. The results also confirm the signalling and legitimacy theory that a company can manage reputational risks through higher voluntary risk disclosure. Practical implications: The corporations managers can gain insights from the studys findings and proactively address cybersecurity risks through strategic disclosure and management practices. In addition, organizations can recognize that investors value transparency and establish a positive reputation for those who communicate openly. Social implications: A significant association between VCRR and corporate reputation implies that such disclosures enhance trust and transparency in the business sector and induce security and accountability among investors engaging with the company. Originality/value: To the best of the authors knowledge, this study is the first that empirically investigates this issue and adds to the international literature a new explanatory variable, corporate reputation, to explain VCRR practices. 2024, Emerald Publishing Limited. -
Navigating the need for accessible labelling through the narratives of consumers with visual impairment in India
This study aims to understand the strategies consumers with visual impairment (CWV) use in acquiring product information and explores preferences for accessible labelling and its benefits. This study employed the qualitative approach of thematic analysis. A snowball sampling technique was used to recruit participants. Data were collected from CWV through semi-structured interviews. The sample size of this study was 12. The data were analysed using NVivo software. The study revealed three strategies used by CWV to obtain product information, namely reliance on caregivers, staff, and technology. However, all the strategies employed have multiple drawbacks. The study reported a high preference for accessible labelling in braille and quick response (QR) codes. Implementing a combination of braille labels and QR codes on product packages was the most beneficial strategy for CWV. The Implementation of accessible labels ensures inclusion in the marketplace. The Author(s) 2024. -
The Problem of Perception in Sandor Mais Embers: An Advaitic Study
This article attempts to study the problem of perception in Sandor Mais celebrated novel Embers from the standpoint of the pramana (a method of knowledge) of Advaita Vedanta. An epistemic problem, the problem of perception, concerns the overwhelming questions of life, culminating in an enigmatic amalgamation of dilemmas and paradoxes. Genuine dilemmas and paradoxes problematize human relationships, which is evident in the complex narrative of Embers. Our contention in this article is to show how, even though enacted within the periphery of the purely fictional, Embers bears testimony to the complexities of life that are quickened by the limits of human perception, which keeps one from seeing how things really are by creating a shadow or reflected consciousness. Set against the backdrop of the Austro-Hungarian Empire, the novel opens up a dialogic space at the intersection of a triangular relationship enacted on the threshold of perception and its multidimensional problems. 2024 Management Centre for Human Values. -
Brain Tumor Classification Using an Ensemble of Deep Learning Techniques
The article reflects on the classification of brain tumors where several deep learning (DL) approaches are used. Both primary and secondary brain tumors reduce the patient's quality of life, and therefore, any sign of the tumor should be treated immediately for adequate response and survival rates. DL, especially in the diagnosis of brain tumors using MRI and CT scans, has applied its abilities to identify excellent patterns. The proposed ensemble framework begins with the image preprocessing of the brain MRI to enhance the quality of images. These images are then utilized to train seven DL models and all of these models recognize the features related to the tumor. There are four models which are General, Glioma, Meningioma, and Pituitary tumors or No Tumor model, which helps in reaching a joint profitable prediction and concentrating solely on the strength of the estimation and outcome. This is a significant improvement over all the individual models, attaining a 99. 43% accuracy. The data used in this research was gotten from Kaggle website and comprised of 7023 images belonging to four classes. Future work will focus on increasing the dataset size, investigating additional DL architectures, and enhancing real-Time detection to improve the accuracy of diagnostic scans and their overall relevance to clinical practice. 2013 IEEE. -
MADeGen: Multi-Agent based Deep Reinforcement Learning for Sequential Keyphrase Generation
Keyphrase generation is an essential tool in the field of natural language processing for information retrieval, document summarization, and text recommendation applications, extracting succinct and representative phrases from the text document. Traditional keyphrase extraction methods applied the supervised or unsupervised learning fail to capture the sequential keyphrase generation in a dynamic environment. The keyphrase generation approaches lack focus on explicitly discriminating the present and absent keyphrases, leading to the inadequate generation of semantically rich absent keyphrases. Hence, this work utilizes the potential benefits of reinforcement learning with the design of a distinguished reward function for present and absent keyphrases for sequential decision-making in the keyphrase generation. Thus, this work presents a novel keyphrase generation system, MADeGen, utilizing Multi- Agent Deep Reinforcement Learning (MADRL). In particular, a multi-agent reinforcement system collaboratively enables the generation of representative and coherent keyphrases by the evaluation metric-aware cooperative reward function analysis and adaptively training the agents. The proposed MADeGen incorporates two major phases, such as multi-agent modelling and actor critic-based policy optimization towards accurate keyphrase generation. In the first phase, the proposed approach designs two learning agents, including the extraction agent and generation agent, with the incorporation of a pre-trained language model. In the multi-agent system, the generation agent is the finetuned version of the extraction agent with the integration of the Wikipedia source. Secondly, the evaluation-aware adaptive reward function is designed to evaluate each agent's generated keyphrases with reference to ground-truth keyphrases. In subsequence, the cooperative reward analysis triggers the actor critic-based policy optimization for the generation agent in the multi-agent system to precisely generate the semantically relevant keyphrases with the assistance of an external web source. Experimental results on several benchmark datasets, such as Inspec, PubMed, and wiki20, illustrate the effectiveness of the proposed MADeGen compared to the existing keyphrase extraction models, yielding state-of-the-art performance in keyphrase extraction tasks. The proposed MADeGen proves its higher performance in the present as well as absent keyphrase extraction as 0.367 and 0.438 F1-score, respectively, while testing on the Inspec dataset. (2024), (Intelligent Network and Systems Society). All Rights Reserved. -
The impact of the COVID-19 pandemic on e-learning adoption in an emerging market: a longitudinal study using the UTAUT model
Purpose: The COVID-19 pandemic provided unprecedented impetus to the evolution of the e-learning learning ecosystem by compelling students to adopt e-learning systems. This paper aims to use the UTAUT model to provide insight into the differences in factors influencing the adoption of e-learning systems before and after the pandemic. Design/methodology/approach: This longitudinal study uses two surveys conducted among graduate students in the city of Bengaluru in India. One prior to the start of the COVID-19 pandemic and a second in its aftermath. PLS-SEM is used to analyze both data sets to draw insights into the constructs that influence Behavioral intention to adopt e-learning systems. The moderating effect of gender is also analyzed. Findings: Pre COVID-19, Facilitating Conditions, Performance Expectancy and Effort Expectancy (quadratic behavior) were dominant factors influencing the adoption of e-learning technologies. Post pandemic, Performance Expectancy and Social Influence are drivers of e-learning adoption. Effort Expectancy and Facilitating Conditions grouped as Ease of Use is a significant driver of e-learning adoption post pandemic. Gender is found to not have a moderating influence. Originality/value: The unique longitudinal study of the differences in factors influencing students intention to adopt e-learning pre- and post-COVID-19 can prove useful to policy makers in the higher education sector. Academics can use the post-pandemic e-learning models findings in multiple contexts such as generational cohorts, educational contexts and social contexts. 2024, Emerald Publishing Limited. -
Esther reimagined: feminist essence in Sara Josephs narrative
Gynocentric approaches to biblical women uncover narratives of liberation and empowerment. These perspectives highlight the gaps and omissions in the representation of women within the overarching metanarrative of the Bible. Sara Josephs novel, Esther, serves as a feminist reimagining of the biblical story of Esther, offering a pluralistic lens through which to examine the experiences and lives of women against the backdrop of patriarchy. This paper utilises the feminist hermeneutic method to critically engage with the narrative, drawing on the feminist frameworks established by scholars such as Elizabeth Fiorenza and Esther Fuchs. It argues that biblical women can be reinterpreted as positive role models, saviours, heroines, and vital contributors to an extraordinary narrative of survival and redemption. 2024 Informa UK Limited, trading as Taylor & Francis Group. -
Exploring the factors of learning organization in school education: therole of leadership styles, personalcommitment, andorganizational culture
Purpose: This study aims to test the conceptual model of the factors of learning organization and explore the degree of mediation of organizational culture in the relationship between leadership styles, personal commitment, and learning organization in school education. Design/methodology/approach: The learning organization profile (LOP) and OCTAPACE profile served to measure learning organization and organizational culture, respectively. The researchers developed scales to measure principals leadership styles and teachers personal commitment. Data included 750 school teachers. Findings: This study found a good fit in the proposed conceptual model. The organizational culture had a significant mediating effect on the path of leadership styles and learning organization and a significant mediating effect on the path of personal commitment and learning organization. Originality/value: To promote a more comprehensive learning culture, school principals should consider two specific organizational mechanisms: the intangible cultural components (such as corporate values, beliefs, and norms) and the tangible structural components (such as organizational structure and workflow systems). These two domains play a crucial role in creating a conducive learning environment. 2024, Jacqueline Kareem, Harold Andrew Patrick and Nepoleon Prabakaran. -
Accumulation of heavy metals (Cr, Cu, As, Cd, Pb, Zn, Fe, Ni, Co) in the water, soil and plants collected from Edayar Region, Ernakulam, Kerala, India
The accumulation of heavy metals in the environment is a significant concern due to their potential toxicity and persistence. This study investigates the levels of heavy metal contamination in the water, soil and plants of the Edayar region in Ernakulam, Kerala, India. The region has experienced industrialization and urbanization, leading to concerns about heavy metal pollution. The study aims to assess the concentrations of chromium (Cr), copper (Cu), arsenic (As), cadmium (Cd), lead (Pb), zinc (Zn), iron (Fe), nickel (Ni) and cobalt (Co) in water, soil, aquatic and terrestrial plants. Samples were collected from various locations within the Edayar region, and Inductively Coupled Plasma Mass Spectrometry (ICP-MS) was conducted to quantify heavy metal concentrations. The findings of this study will contribute to the assessment of heavy metal pollution in the Edayar region. Plants with a high diversity index were taken for analysis from both aquatic and terrestrial habitats. Scoparia dulcis L. seems to specialize in metal accumulation, possibly for protective purposes. Synedrella nodiflora Gaertn demonstrates adaptability to metal-rich environments through robust metal uptake and tolerance mechanisms. Alternanthera philoxeroides (Mart.) Griseb, on the other hand, appears to have developed mechanisms to manage heavy metal exposure. The results indicate significant levels of heavy metal contamination across all samples, with the highest concentrations detected in soil, followed by water and plants. Chromium and lead levels in soil exceeded the permissible limits set by international standards, posing potential risks to human health and the ecosystem. The accumulation patterns in plants varied, with higher bioaccumulation factors observed for zinc and copper, suggesting their preferential uptake. This study highlights the urgent need for remediation strategies and continuous monitoring to mitigate the impact of heavy metal pollution in the Edayar region. The results will help in understanding the environmental impact of human activities. Copyright: The Author(s). -
Efficient one-pot green synthesis of carboxymethyl cellulose/folic acid embedded ultrafine CeO2 nanocomposite and its superior multi-drug resistant antibacterial activity and anticancer activity
Due to the prevalence of drug-resistant bacteria and the ongoing shortage of novel antibiotics as well as the challenge of treating breast cancer, the therapeutic and clinical sectors are consistently seeking effective nanomedicines. The incorporation of metal oxide nanoparticles with biological macromolecules and an organic compound emerges as a promising strategy to enhance breast cancer treatment and antibacterial activity against drug-resistant bacteria in various biomedical applications. This study aims to synthesize a unique nanocomposite consisting of CeO2 embedded with folic acid and carboxymethyl cellulose (CFC NC) via a green precipitation method using Moringa oleifera. Various spectroscopic and microscopic analyses are utilized to decipher the physicochemical characteristics of CFC NC and active phytocompounds of Moringa oleifera. Antibacterial study against MRSA (Methicillin-resistant Staphylococcus aureus) demonstrated a higher activity (95.6%) for CFC NC compared to its counterparts. The impact is attributed to reactive oxygen species (ROS), which induces a strong photo-oxidative stress, leading to the destruction of bacteria. The minimum inhibitory concentration (MIC) and minimum bactericidal concentration (MBC) of CFC NC are determined as 600g/mL and 1000g/mL, respectively. The anticancer activity against breast cancer cell resulted in the IC50 concentration of 10.8?g/mL and 8.2?g/mL for CeO2 and CFC NC respectively.The biocompatibility test was conducted against fibroblast cells and found 85% of the cells viable, with less toxicity. Therefore, the newly synthesized CFC NC has potential applications in healthcare and industry, enhancing human health conditions. The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature 2024. -
Purification and Biochemical Characterization of Beta-Hexosaminidase B from Freshwater CnidarianHydra vulgaris Ind-Pune
Beta-N-acetylhexosaminidase (Hex) is a vital lysosomal hydrolase found in all living organisms, playing a crucial role in cellular homeostasis. Dysfunctions in this enzyme are implicated in severe pathological conditions such as Tay-Sachs and Sandhoff diseases in humans. In this paper, we report the purification and biochemical characterization of hexosaminidase from the soluble extracts obtained from the polyps of Hydra vulgaris Ind Pune. The Hydra Hex was purified by two-step sequential chromatography (hydrophobic interaction and gel filtration). Our results suggested that the enzyme isoform purified from Hydra is HexB, most likely to be a homodimer with a subunit mass of 65 kD. The pH optimum was in the range of 5.0 to 6.0 and the temperature optimum in the range of 50 C to 60 C. pH stability and temperature stability were found to be 5.0 and 40C respectively. The homology modelling studies corroborated the homodimeric nature of Hydra HexB, and indicated its structural resemblance to human HexB. This study offers new insights into the biochemical characteristics of Hydra HexB, providing a foundational framework for extensive investigations on this and other lysosomal hydrolases in Hydra. In a broader context, our results significantly contribute to establishing Hydra as a potential model organism to study the lysosomal biogenesis pathway. (2024), (Association of Carbohydrate Chemists and Technologists). All Rights Reserved. -
Women entrepreneurs vs. women employees: a comparative study of personality traits and success factors of women in India
In the current study, the researchers evaluate the relationship between personality traits, as defined by the Big Five personality traits, and success factors of women: as entrepreneurs and employees. The findings are based on data collected from 100 women employees and 100 women entrepreneurs. Data was collected using structured questionnaires and analysed using IBM SPSS. The findings suggest that there are statistically significant differences between women entrepreneurs and women employees on certain dimensions of personality. The evaluation of the relationship between the personality traits and success factors revealed that in the case of entrepreneurs, personality traits were significant in predicting success. As nations work to improve gender ratios in the labour force and as the number of women entrepreneurs grows, a better understanding of what constitutes success and the factors that could influence success are critical in supporting female participation in the economy, as entrepreneurs and employees. Copyright 2024 Inderscience Enterprises Ltd. -
Mass layoffs at BYJUS founders dilemma
Learning outcomes: This case study provides students/managers an opportunity to learn about the following: to infer the challenges involved in the downsizing of employees; to asses and evaluate BYJUS organizational culture; and to determine the impact of workplace toxicity. Case overview/synopsis: The focus of this case is the controversy faced by BYJUS due to its mass layoffs and toxic work culture. This case discusses the CEOs dilemma in resolving the controversy. Two rounds of mass layoffs at BYJUS are discussed in detail. The industrial dispute filed by Employees Union against BYJUS accusing it of denying due compensation to laid-off employees is also discussed. This case consists of a section explaining the toxic work culture at BYJUS, which is supported by employee complaints. The CEOs justification and apology have been illustrated in this case. The case ends with a closing dilemma and challenges faced by the CEO. Complexity academic level: The case is best suited for undergraduate students studying Human Resources Management subjects in Commerce and Business Management streams. The authors suggest that the instructor inform students to read the case before attending the 90-min session. It can be executed in the classroom after discussing the theoretical concepts. Supplementary material: Teaching notes are available for educators only. Subject code: CSS 6: Human Resource Management. 2024, Emerald Publishing Limited.