Impact of Corporate Governance on Organisational Performance of Indian Firms

This research study explored the link between corporate governance practices (CGPs) and organisational performance in India, especially in the context of some major CG reforms that have been undertaken since the turn of the twenty-first century. The authors also attempted to understand in-depth the implications of these reforms for the companies. For assessing the link between CG practices and organisational performance, data were collected from a sample of 100 listed companies in India using an adapted version of the Institute of Company Secretaries of India (ICSI)’s questionnaire. Multilevel Factor Analysis (MFA) for scores along 5 CG sub-categories revealed 17 first-level and 4 second-level factors. Regression of organisational performance, measured using Compound Annual Growth Rate (CAGR), against these factors showed that the first-level factor representing corporate social responsibility and sustainability (CSRS) was a significant predictor of organisational performance. This finding is significant while considering the introduction of mandatory CG provisions for corporate social responsibility (CSR), applicable to companies meeting specified turnover and profitability thresholds according to CG regulations in India. The findings of this study open the debate on CG regulation and on mandatory and desirable norms in the Indian context. Eligible Indian companies must focus on the CG practice of investing in CSR initiatives through purpose-led CSRS interventions and their long-term benefits, rather than on viewing it as a mandatory CG provision that induces short-term expenses.

Multilevel factor analysis of flipped classroom in dental education: A 3-year randomized controlled trial

Purpose Previous studies have rarely attempted to test the confounding factors that may affect learning outcomes of the flipped classroom. The purpose of this study was to assess how flipped classrooms affect the acquisition of knowledge in clinical dental education based on multilevel factor analysis. Method The authors conducted a 3-year (2017, 2018, and 2019) randomized controlled trial in a series of introductory prosthodontics courses in dental education. A total of 137 participants were randomly assigned to flipped classroom (n = 70, 51%) or lecture (n = 67, 49%) formats. The flipped group was instructed to self-learn knowledge-based content through online preparation materials, including videos and text, while the lecture group was given text only. Both groups were provided with the same study content and opportunities for different styles of learning. The session attendance rate and number of times the materials were accessed were monitored. Individual and team readiness assurance tests (IRAT/TRAT) were conducted to evaluate knowledge acquisition. A multilevel linear regression analysis was conducted on both instructional styles (flipped vs. lecture) as an intervention factor, and confounding factors that could affect the outcomes were implemented. Results The average number of online accesses was 2.5 times per session in the flipped group and 1.2 in the lecture group, with a significant difference (p < .05). The average IRAT score was significantly higher in the flipped than in the lecture group (effect size [ES] 0.58, p < .001). The number of online accesses was significantly and positively correlated with IRAT scores (0.6 [0.4, 0.8]). The instructional style was significantly and positively correlated with TRAT scores (coefficient [95% confidence interval]: 4.6 [2.0, 7.3]), but it was not correlated with IRAT (4.3 [-0.45, 9.0]). Conclusions The flipped classroom was more effective than the lecture format regarding knowledge acquisition; however, the decisive factor was not the instructional style but the number of individual learning occasions. The employment of the flipped classroom was the decisive factor for team-based learning outcomes.

Development of multifactor index for assessing quality of life of a tribal population of India: multilevel analysis approach

Background The main objective of this study is to develop a multilevel multi-factor index to assess the quality of life of the Malayali tribal population of India at the household and village levels based on nine domains, namely, Demography, Economy, Health, Human Development, Infrastructure Development, Work Participation, Recreation, Social Capital and Self Perception. An attempt is made to classify the individuals as well as villages by the overall scores of a multi-factor -index within a community which will help policymakers to develop concrete policy recommendations for the improvement of the quality of life of this tribal group. Method Multilevel factor analysis is utilized to determine uncorrelated meaningful factors and their respective weights using Mplus software from the nested dataset consists of values of nine domains of 1096 individuals collected from 19 villages. A multilevel multi-factor index is constructed using the weights of these factors. The qualities of the lives of different households and different villages are assessed using the scores of this index. Results Three different factors are identified at household as well as village levels. The quality of life at Households and Village levels are classified as poor, low, moderate, good, and excellent based on five quintiles of the scores of the multi-factor index, and the contribution of each domain in this classification is ascertained. Discussion This study finds that at household as well as at village levels, the quality of life of the individuals of this tribal population increases with an increase in education, income, and occupation status which make them lead a healthy life and also make them to find time and money to spend on recreation. Infrastructure is not important at the household level but not so at the village level. Conclusion The main purpose of developing this kind of multi-factor index at different levels is to provide a tool for tribal development based on realistic data that can be used to monitor the key factors that encompass the social, health, environmental, and economic dimensions of quality of lives at the household and community levels of these tribal people.

Development of Multifactor Index for Assessing Quality of Life of a Tribal Population of India: Multilevel Analysis Approach

BackgroundThe main objective of this study is to develop multilevel multi-factor index to assess the quality of life of Malayali tribal population of India at the individual and village levels based on nine domains, namely, Demography, Economy, Health, Human Development, Infrastructure Development, Work Participation, Recreation, Social Capital and Self Perception. Also, an attempt is made to classify the individuals as well as villages on the basis of the overall scores of multifactor index within a community which will help policy makers to develop concrete policy recommendations for the improvement of quality of life of this tribal group.MethodMultilevel factor analysis is utilized to determine uncorrelated meaningful factors and their respective weights using Mplus software from the nested dataset consists of values of nine domains of 1096 individuals collected from 19 villages. Multilevel multifactor index is constructed using the weights of these factors. The qualities of lives of different households and of different villages are assessed using the scores of this index.ResultsThree different factors are identified at household as well as village levels. The quality of life at Households and at villages levels are classified as poor, low, moderate, good and excellent based on five quintiles of the scores of the multifactor index and the contribution of each domain in this classification is ascertained.DiscussionThis study finds that at household as well as at village levels, the quality of life of the individuals of this tribal population increases with increase in education, income and occupation status which make them to lead a healthy life and also make them to find time and money to spend on recreation. Infrastructure does not play a significant role at the house hold level whereas it is a matter at village level. ConclusionThe main purpose of developing this kind of multifactor index at different levels is to provide a tool for tribal development based on realistic data which can be used to monitor the key factors that encompass the social, health, environmental and economic dimensions of quality of lives at the individual/household and community levels of this tribal people.

More (of the right strategies) is better: Disaggregating the naturalistic between- and within-person structure and effects of emotion regulation strategies

Although people often use multiple strategies to regulate their emotions, it is unclear if using more strategies effectively changes emotional outcomes. This may be because there is no clear, data-driven structure to organise which strategies people use together, so strategies with opposing impacts are modelled together. We first conducted a multilevel factor analysis of negative- and positive-emotion regulation strategies among undergraduates (n = 92) completing ecological momentary assessment three times per day for 10 days. Solutions including 3-within/3-between factors were most interpretable. Using more between-person Adaptive Engagement strategies and within-person Adaptive Engagement, Enhancement, and Behavioural strategies predicted improved mood, whereas using more between-person Aversive Cognitive and within-person Aversive Cognitive and Disengagement strategies predicted worse mood, ps &lt; .05. Using a greater quantity of strategies may thus promote better, or worse, emotional outcomes, depending on the class of strategies used.