The effect of efficiency on shareholder activism (SHA) with the moderating effect of Return on Assets (ROA) has been studied by this research study. This analysis uses data about corporate firms from the CMIE Prowess database. This data spans over 4 years from 2016 to 2020. Static panel data are used to propose the two models (base model and the interaction model). The application of PDR models from this study shows that Efficiency impacts SHA negatively. The influences of efficiency on shareholder activism are multifaceted and dynamic. The association of shareholder activism and the efficiency of the organization is not significantly influenced by the moderating variable which is the return on assets for the selected dataset of this study. As the chosen data represents a significant segment of the Indian corporate landscape, this study offers a better understanding of how efficiency relates to SHA within corporates in the Indian context. The results of this study can provide guidelines for strategy preparations to proactively demeanor the issues of shareholder activism in the context of fast fast-changing technology landscape and its use by new age activist.

This study investigates the influence of Corporate Social Responsibility (CSR) on sustainable development in India, specifically analyzing the literacy rate's moderating role. Utilizing a quantitative approach through Panel Data Regression Analysis (PDRA) on secondary data, the research is confined to India. Despite this limitation, the study serves as a valuable foundation for future research. The geographical restriction not only provides context-specific insights but also lays the groundwork for broader comparative analyses in diverse global contexts, suggesting avenues for expanding the research agenda.

This research aims to assess the effect of the promoters on the liquidity of Indian banks using the Net Stable Funding Ratio (NSFR) as a variable. The risk-weighted assets (RWA) are used as a moderator to assess their effect on NSFR and promoter. The data is analyzed by using the panel data method (PDM). 31 Indian banks were taken as samples in this study for the period from 2010 to 2019. It is observed that the base model shows a positive association between promoters and NSFR, it signifies that an increase in promoter value increases NSFR. In the second model, the impact of a moderator (RWA) is observed on NSFR and promoter and finds a significant and positive association between them. From the implications point of view, the study's findings will aid policymakers in comprehending how changes in promoters impact the NSFR and overall banking industry. The study is unique in the sense that there are rarely any studies being done to assess the relationship between NSFR and promoter. The study also lays the foundation for further studies concerning NSFR, RWA, and promoters.

This study examines the nexus between environmental indices and governance about dividends within the Indian banking sector, incorporating Non-Performing Assets (NPA) as a moderator. The investigation spans the period from 2010 to 2019 and encompasses a sample of 33 representative Indian banks. Data retrieval is executed through Prowess and the authorized websites of individual banks. Four models, comprising two bases and two interaction models, are formulated for analysis. Regression analyses underscore the noteworthy influence of both base models on dividend outcomes. The findings further indicate that elevated levels of bank NPAs disrupt the correlation between the governance index and dividend distributions. Nevertheless, the analysis indicates an absence of moderating influence by NPA on the relationship between the environmental index and dividends. Through an in-depth examination of the Indian banking sector utilizing a substantial sample, this research contributes to the existing literature by shedding light on the impact of environmental and governance policies on a company's dividend policy.

Many research studies on LCR (Liquidity Coverage Ratio) and bank efficiency have commonly examined the relationship between a bank's liquidity management and overall performance. This study used the panel data method to analyze the result. The efficiency is measured by using the Data Envelopment Analysis approach. This study reveals the moderating effect of RWA (Risk Weighted Assets) on the relationship between LCR and the efficiency of the banks post Covid-19 scenario for Indian banks. The research design presents a conceptual framework with liquidity as the dependent variable and defines the hypothesis based on the framework. The two models—Base and Interaction, are defined using variables, and the hypothesis is tested using the interaction model. The interaction model demonstrates the moderating impact of risk-weighted assets in the relationship between efficiency and liquidity. This study confirms that risk-weighted asset increases result in an increase in the values of liquidity along with efficiency. The study’s originality lies in the type of models (base and interaction) defined considering the log value of sales and assets. So, such a robust model helps to get the perfect results for all uncertain and stressful situations in banking environments.

The current research focuses on financial technology’s and digitization’s effects on rural sustainable development, and the rural sector is playing a very important role to increase sustainable growth in India. Also, this investigation looked at secondary data from 29 Indian states and two union territories during three fiscal years, from 2018 to 2020. In this study, panel data analysis is used to evaluate the hypothesis (PDA). Hence, financial technology and digitalization have a good effect on rural development in India. The financial technology and digitalization of the rural sector of India are playing a vital role in economic development in India. Thus, extension plans should integrate the public, corporate, and non-governmental (NGOs) sectors in order to promote and execute FPOs. Governmental organizations ought to support the creation and administration of FPOs. For FPOs to boost agricultural profitability by assisting farmers in obtaining more consumer rupees, extension workers should possess facilitation abilities.

This research aims to study the relationship between financial inclusion efficiency (FIE) and poverty score. The data for this research includes 28states and 3 union territories of India. A data envelopment analysis (DEA) is a popular and effective tool revealed by literature research studies to assess countries' financial inclusion levels. This study used a panel data model with DEA wherethe Poverty Score (PS) is presented as the dependent variable, and the independent variables selected are Financial Inclusion Efficiency (FI_CRS), Number of ATMs (No_ATM), and Literacy Rate (Lit_rt). From the optimal weights of the DEA model, descriptive statistics, correlation matrix scores, and endogeneity test results, the results of the study show that there is a significant impact on poverty scores by financial inclusion efficiency. The Financial Inclusion Efficiency (FI_CRS) is significant and negative which signifies that there is a negative relationship between Financial Inclusion Efficiency (FI_CRS) and Poverty Score (PS). Thus, this research shows that the rise in fie resulted in a decrease in the Poverty Score of 28 Indian states and 03 union territories.

This paper examines the relationship between Distribution and Promotional expenditure on the profitability of pharmaceutical firms in India using data collected from 137 pharmaceutical companies working in the Indian economy from 2017 to 2022. The study employs a panel data model analysis with Distribution and promotional expenditure as the independent variables, Operating Profit and Profit after Tax as the dependent variable, and Sales as the Control Variable. The analysis's results show that the independent variable has a substantial influence on the dependent variable, as shown by the significant p-values for the coefficients of selling expenditures and ln sales, respectively, and the R-square and SE values of.7662 and 3604.2096, respectively (operating profit). Academicians could use the study in this work to more critically assess how well the endogenous growth model applies to pharmaceutical companies and to acquire more empirical data to back up our findings.

This study is conducted to understand consumers’ preferences with different demographic variables on their car purchase decision based on features the car offers and the cost consciousness variables considered mainly by consumers, as suggested by previous studies on this topic. The judgmental survey method was used for this research using a structured & non-disguised questionnaire to collect the responses. The pilot survey was used to understand the instrument’s reliability and validity total of 200 respondents were contacted, but 143 responses were received. The response rate was almost 72% of the reached respondents. But, only 103 usable responses were considered for analysis as there were 40 responses found not to be a worthwhile while. 13 were inconsistent with their answers, 22 had missing values with essential questions, and the remaining 5 were outliers in their response. The shortlisted sample size (with almost 50% responses) is adequate for this type of research. Factor analysis with PCA is performed to group the variables and define the dependent variables for this study. The two dependent variables were defined from this. They are described as features of the cars and cost consciousness. Then ANOVA is used to get p-values for the regression scores of the independent demographic variables to understand the impact. The findings of this study show that none of the essential demographic variables of consumers (here gender, education, occupation and age) has shown a significant impact with features and cost consciousness as dependent variables in car purchase decisions. These findings contradict the studies done in the past. It is find from this study, that the consumers are more fashion-conscious and environmentally conscious than cost-conscious. This result may be because of the characteristics of the sample, which shows that there is no significant impact of any of the demographic variables on the car purchase decision based on the feature of the car as well as cost-consciousness factors like resale value, maintenance and fuel. The results of this study may change if the sample contains equal percentages of the consumers for all the demographic factors. The results may vary if the sample has more part-time employees and other types such as students, retired and unemployed.

This research paper targets to investigate the influence of ownership concentration (OC) on the dividend policy (DP) of 78 listed non-financial firms. Return on capital (ROC) is used to moderate the relationship between OC and DP. Data collected for analysis pertains to 2016–2020. The methodology adopted for analyzing data of these firms for the said period is the quantile regression panel data model (QRPDM). The models' findings show no significant impact of OC on the DP of these firms; however, under the influence of ROA, the relationship between OC and DP becomes significant. The limitation intrinsic to this study is the non-consideration of financial firms, which paves the way for further work in the area. This study is the first to take up OC, a crucial component of CG, and assess its impact on DP for India specifically.

The ecosystem for digital payments in India has expanded quickly during the last decade. A synthesis of technical advancements and progressive governmental laws and regulations has fuelled this expansion. Particularly, the UPI system has assisted India in transitioning from a nation heavily reliant on cash for daily transactions to one with fewer cash transactions. The study attempted to determine how Financial Inclusion (FI) through a socio-techno-ecosystem impacts digital payment systems. FI involves ensuring financial services, products, and an adequate amount of credit without discrimination against the weaker section of society. The study has established that FI impacts the UPI. The finance infrastructure thus helps to develop an ecosystem where financial access and the awareness level help people to transit to new channels of payment. We have used secondary data of 27 banks for sixteen quarters and four years, i.e., for the financial years 2016-17 to 2019-20. It is observed from the current study that the offsite_ATM plays a significant role in the value creation of the UPI. Our study implies that it will help retailers, individuals, and business houses to use UPI platforms for swift payments without hassle. Also helpful for industries that are still not digitally disrupted and industry-specific UPI transactions.

The ultimate motive of the paper is to establish whether financial inclusion (FI) has a consequential impact on the Sustainable Development (SD) of India. This study uses one model for the assessment of the influence of FI through the Co-Operative bank network on SD. This is purposely done to analyze the absolute impact of the role of the Co-Operative bank network in the said context. The sample encompasses data taken from 28 states and 3 Union Territories for two years (FY2018-FY2020). Assessment of data for the remaining Union Territories is not undertaken for the reason of the non-availability of data for other Union Territories. This study uses Panel Data Analysis (PDA) to establish the nexus of the relation between the said variables. Results of this study reveal elevated levels of SD resultant of increased FI thereby indicating a positive and significant relationship between the said variables. Unlike previous studies, this study gives India-specific significant findings, which suggests policy formulation for increasing the numbers and improving the governance of Co-Operative bank networks for SD. Co-Operative bank network as a proxy despite having high weighted significance in FI has not been incorporated in any recent study as per the last updated knowledge of authors.

Globally, COVID-19 has significantly impacted many different organizations and people. From the banks' perspective, this pandemic has affected banks' corporate and retail customers. Also, banks had to adjust to distributed workforce model. This paper analyses the lessons learned from the COVID-19 pandemic, which can be effectively used to rebuild banks' Operational Risk Management capabilities. The present study used the survey research methodology, which includes structured questionnaires completed by senior banking professionals to analyze the learnings from COVID-19 and understand the distributed workforce model and remote working effectiveness. Findings: The Pandemic accelerated the pace of digital transformation. The lockdown imposed due to the pandemic led to employees working remotely, which has been effective because of enhanced digital capabilities. However, enhanced monitoring is required to prevent data-related issues, and action needs to be taken to address challenges faced in having a remote distributed workforce model, like negative impact on on-the-job learning, data-related risks, and employee wellbeing. COVID-19 is an unprecedented event that could not have been predicted in any scenario analysis. This crisis has highlighted various systemic drawbacks that need to be addressed. Banks can apply the lesson learned from this Pandemic to become more robust in the future.

All Industries and Business People are running behind social media as today’s customers, their suppliers, all prospective employees, and all stakeholders also found on these media platforms. Popular Social media platforms, such as Google Hangout, Twitter, Instagram, Facebook, and LinkedIn, are internet-based applications that build on the societal needs with strong technological foundations for Group communications and exchanges seamlessly. New generation technology-based eLearning platforms are incorporating these social media applications into learning environments also. Thus, they are challenging the status quo of traditional learning modes by using the latest technology innovations, including Social media.cSocial media is about building relationships with improved 24 x 7 communications and more interactively and excitingly learning from others. Hence, it can be used in the learning process to build and grow peer-to-peer interactions and improve peer learning, 24 x 7 Student support and help. “Peer to Peer learning” is a very imperative factor in any teaching and learning process. Information and awareness collected using social media by people can provide useful perceptions about various matters more than the traditional pedagogy with brick-andmortar structure. It can also be used for peer evaluations and determine one’s performance in the group study. The usage of social media has been growing in everybody’s life, and learning should not be an exception for the same. Some years back, it was considered bad to use social media, but today everybody is looking from another side. Universities and Institutions with their vibrant faculty/staff teams are adapting these changing needs of the new paradigm shift in Learning Settings and becoming primary adopters. Initial adopters have the early lead and reasonable advantage also. Today’s most prevalent social networks are Facebook, Twitter, and LinkedIn, used by the majority of people when you consider social media. The true social media experience is much larger than it is explored by many. These platforms can involve and engage students using Smartphone apps by developing interactive Android Apps, which can be used anytime and anywhere by the students. This research provides a comprehensive literature review of such tech-savvy University and Institution approaches and their value proposition for being competitive in this Digital Era using these Online and Social Media Platforms successfully to find out attractions and capabilities available in these media platforms.

E-Learning is an essential activity as witnessed by many experts for competitive advantage in university systems now. Many universities across the world want to progress in their e-Learning creativities and LMS platform, which would be very useful to achieve the gross enrollment ratio (GER) as targeted by their counties Student support in the e-Learning course setting has a significant role and is an essential component (Chen et al. 2010). Sener and Humbert (2003); learner fulfillment in these settings is a vital component. Students' contentment finally leads to completion of the course in any format of the learning. This paper ranks the essential elements of student support in e-Learning courses using the AHP model based on the results. This model ranks five important attributes taken from literature: Student Attributes, Technology Attributes, Economic Attributes, Design Attributes, and Interactivity Attributes. The findings of this study suggest that appreciating student variables like self-confidence, inspiration, and perceived value about courses are very significant. The results of this study reveal that the system's Student Attribute is seen as the most important, followed by the system's Technology Attribute. The Interactivity Attribute is ranked 3rd , and Design and Economic Attribute is at 4th and 5th place. These results infer that to improve the effectiveness of learner provisions, variables like self-confidence of the learner, stimulus to join the course, and perceived worth of the system in the learner's mind is vital. This study is helpful for institutions and e-Learning Course developers to design Student Support based on a hierarchy of the attributes and formula tea strategy to improve the student support for better results.

PurposeFirms use design capability across the globe to compete and increase sales, e.g. Apple. However, the payoff from design know-how has been overlooked thus far. Academic research lags in this space despite the intersection of sales, technology and design in practice. This paper provides researchers and managers with implications of the interplay between design capability and technological market conditions to enhance a firm's sales.Design/methodology/approachFirms' capability design, and sales impact have been studied in this paper across different technological market conditions. Primary technological conditions of the industry under which firms operate are captured, which are technological intensity (TI), technological competitive intensity (TCI) and technological maturity (TM). Their interplay has been studied using panel data analysis, examining fixed and random effects.FindingsDesign is an important, interesting and non-imitable capacity that yields positive firm execution results. It provides an urgent differentiator and improves deal development. This study found that all four hypotheses are generally supported. The main finding is that, provided underlying technology is good, design significantly improves sales, but design alone cannot substitute for poor technology.Practical implicationsThe results of this study link the three technological environment conditions, namely, TI, TCI and TM with sales growth. The authors find that design can and does add to superior performance, provided technological excellence exists prior. But, in the absence of good technology, design alone will hinder performance.Originality/valueThis paper examines the effect of firm design capability on sales growth. The paper finds a positive moderating effect of TCI and TM but a negative moderating effect of TI. The researchers believe these aspects of the design have not been studied before.

Consumers have their own preferences when it comes to shopping modes, be it offline or online. Factors such as touch and feel of the product, instant gratification, delivery times are few which effect the consumer to either shop offline or online. Due to the recent outbreak of the corona pandemic, the entire supply chain had been disrupted and the transmission modes of the virus and norms of social distancing may shift the preferences of the consumer with respect to the way groceries are being shopped. This paper accounts to the study the probable shift in the consumer preferences caused due to the COVID-19 pandemic. Factors that influence the consumer to shop offline and online during the pandemic are ranked according to the responses received by using mean scoring techniques. Chi-square statistical analysis has been used to find out the statistical significance in relationship between the change in consumer preferences caused by the COVID-19 pandemic.