Business Perspectives and Research, Ahead of Print.
Agriculture in India is undergoing a shift. It is due to a grim situation of increasing food production and rural economy linked with agriculture. On one side, agriculture production is led by 55% of cereal crops primarily based on minimum support prices (MSPs) by the Government of India. On the other side, horticulture accounts for only 16% of agriculture without many incentives. The cultivation cost is rising day by day. Unlike employee compensation, the market does not support farmers and their products. Despite rising production, sustainable agricultural growth is unlikely because of issues including groundwater depletion, climate change, and poor income. The MSP is driving the change in farmer’s lives in the changing nature of rural economy. However, the economic conditions of farmers have not changed much as the surveyed households (HHs) revealed based on MSP and its significance on economic condition of farmers. About 60% of farmers claimed that their income remained the same, 22% said that their condition got better, while about 14.43% of HHs claimed that their economic situation got worst. The study highlights that sustainable agriculture and changing nature of the rural economy will transform farmers’ conditions if they diversify the production of crops from cereals to non-cereal crops such as protein-based pulses or less water intensive crops such as millets.
Category Archives: Business Perspectives and Research
Assessing the Effects of Customer-perceived Values Toward Organic Food: The Moderating Role of Media Exposure to Food Safety Issues
Business Perspectives and Research, Ahead of Print.
Despite a plentiful supply of organic food in emerging economies, consumers are slow to adopt sustainable organic food behaviors. India is one of the top five nations in the world in terms of the total amount of agricultural land that is certified as organic, but the domestic organic consumption in the country itself is really sparse. Using the framework of the theory of reasoned action, this investigation explores how customers’ perceived values (health and hedonic values) influence their attitude toward purchasing organic food. Also, it elaborates on the moderating effect of media exposure to food safety issues to know its strength in the attitude–intention relationship. This research utilized PLS-SEM to analyze the structural relationships among the constructs, with 202 responses from consumers in India. The study found the strongest influence of hedonic value over health value and subjective norms on the green purchase attitude of consumers. To the best of our knowledge, this is the first study that investigated the moderating effect of media exposure on food safety issues on consumers’ attitude–intention relationship in a developing nation context. The study highlighted that people who have regularly been exposed to food safety related issues around them are more willing to buy organic food. Thus, it contributes to a more robust attitude–intention relationship among customers toward the purchase of organic food.
Despite a plentiful supply of organic food in emerging economies, consumers are slow to adopt sustainable organic food behaviors. India is one of the top five nations in the world in terms of the total amount of agricultural land that is certified as organic, but the domestic organic consumption in the country itself is really sparse. Using the framework of the theory of reasoned action, this investigation explores how customers’ perceived values (health and hedonic values) influence their attitude toward purchasing organic food. Also, it elaborates on the moderating effect of media exposure to food safety issues to know its strength in the attitude–intention relationship. This research utilized PLS-SEM to analyze the structural relationships among the constructs, with 202 responses from consumers in India. The study found the strongest influence of hedonic value over health value and subjective norms on the green purchase attitude of consumers. To the best of our knowledge, this is the first study that investigated the moderating effect of media exposure on food safety issues on consumers’ attitude–intention relationship in a developing nation context. The study highlighted that people who have regularly been exposed to food safety related issues around them are more willing to buy organic food. Thus, it contributes to a more robust attitude–intention relationship among customers toward the purchase of organic food.
Investors’ Irrational Sentiment and Stock Market Returns: A Quantile Regression Approach Using Indian Data
Business Perspectives and Research, Ahead of Print.
Studying sentiment is crucial for investors and portfolio managers to determine whether sentiment can be used as information to make profits. This study examines the relationship between irrational sentiment among investors and excess returns in the Indian stock market using monthly data from July 2001 to December 2019. The study constructs a composite sentiment index that includes condensed information from 10 variables. The empirical analysis reveals that the influence of irrational sentiment among investors on excess returns in the stock market is not uniform across quantiles. Specifically, our results indicate that the irrational sentiment index has information regarding contemporaneous (future) variation in excess returns in upper (all) quantiles. Results also suggest that the predictive ability of irrational sentiment is enhanced when market conditions are right. We also decompose the sentiment into positive and negative irrational sentiment and find an asymmetrical impact in upper quantiles but lost at lower quantiles.
Studying sentiment is crucial for investors and portfolio managers to determine whether sentiment can be used as information to make profits. This study examines the relationship between irrational sentiment among investors and excess returns in the Indian stock market using monthly data from July 2001 to December 2019. The study constructs a composite sentiment index that includes condensed information from 10 variables. The empirical analysis reveals that the influence of irrational sentiment among investors on excess returns in the stock market is not uniform across quantiles. Specifically, our results indicate that the irrational sentiment index has information regarding contemporaneous (future) variation in excess returns in upper (all) quantiles. Results also suggest that the predictive ability of irrational sentiment is enhanced when market conditions are right. We also decompose the sentiment into positive and negative irrational sentiment and find an asymmetrical impact in upper quantiles but lost at lower quantiles.
Exploring the Determinants of Investment Behavior: Evidence from Agrarian Investor Class of India
Business Perspectives and Research, Ahead of Print.
The current research aims to identify the factors that influence the investment behavior of the agrarian investor class, an untapped potential segment for the investment market, in India. The study observes the antecedents of investment behavior and intention. Thus, the present study analyses the responses of 400 agrarian rural respondents. Data from a well-structured questionnaire administered to the study’s target participants were analyzed using structural equation modeling. The results observed the utmost influence of financial self-efficacy in establishing the agrarian rural investors’ attitude and has least influence in determining personality traits and financial knowledge, which ultimately determine the investment intention of investors. Further, social influence has the least effect on how agrarian rural people think and act. The findings demonstrate that investment intention is the leading factor in cementing the investment behavior of agrarian rural investors. This article claims its distinctiveness by adding important insights to the literature of the investment behavior and intention for the Indian agrarian investor class.
The current research aims to identify the factors that influence the investment behavior of the agrarian investor class, an untapped potential segment for the investment market, in India. The study observes the antecedents of investment behavior and intention. Thus, the present study analyses the responses of 400 agrarian rural respondents. Data from a well-structured questionnaire administered to the study’s target participants were analyzed using structural equation modeling. The results observed the utmost influence of financial self-efficacy in establishing the agrarian rural investors’ attitude and has least influence in determining personality traits and financial knowledge, which ultimately determine the investment intention of investors. Further, social influence has the least effect on how agrarian rural people think and act. The findings demonstrate that investment intention is the leading factor in cementing the investment behavior of agrarian rural investors. This article claims its distinctiveness by adding important insights to the literature of the investment behavior and intention for the Indian agrarian investor class.
Predicting the Symmetric and Asymmetric Volatility of Energy Market: Evidence from COVID Outbreak in India and USA
Business Perspectives and Research, Ahead of Print.
The COVID-19 pandemic had a tremendous impact on the energy sector because of demand factor. Volatility has emerged as a major concern in the energy industry and COVID-19 has cast a dark shadow over this characteristic. We predict the symmetrical and asymmetric volatility of energy market in India and USA during COVID-19 outbreak tenure. The energy market is proxied by crude oil and natural gas of these two countries. For an empirical estimation, standard generalized autoregressive conditional heteroscedasticity (s-GARCH) and exponential GARCH (e-GARCH) are employed based on daily observations spanning from March 25, 2020 to January 31, 2022. The result reveals that new information is captured and there is volatility persistence in both Indian and US energy markets. The conditional volatility decays over the time of these markets since it is backed by mean reversion and Indian energy market decays fast comparatively. Additionally, it depicts that there is no leverage effect in both Indian and US energy markets. This study furnishes an insight to the investors and portfolio managers with respect to risk prediction considering impact of good and bad news.
The COVID-19 pandemic had a tremendous impact on the energy sector because of demand factor. Volatility has emerged as a major concern in the energy industry and COVID-19 has cast a dark shadow over this characteristic. We predict the symmetrical and asymmetric volatility of energy market in India and USA during COVID-19 outbreak tenure. The energy market is proxied by crude oil and natural gas of these two countries. For an empirical estimation, standard generalized autoregressive conditional heteroscedasticity (s-GARCH) and exponential GARCH (e-GARCH) are employed based on daily observations spanning from March 25, 2020 to January 31, 2022. The result reveals that new information is captured and there is volatility persistence in both Indian and US energy markets. The conditional volatility decays over the time of these markets since it is backed by mean reversion and Indian energy market decays fast comparatively. Additionally, it depicts that there is no leverage effect in both Indian and US energy markets. This study furnishes an insight to the investors and portfolio managers with respect to risk prediction considering impact of good and bad news.
Editorial
Business Perspectives and Research, Volume 11, Issue 3, Page 335-335, September 2023.
The Impact of Group Support on College Student’s Online Business Motivation: The Uncertainty Avoidance Thinking as a Moderating Factor
Business Perspectives and Research, Ahead of Print.
This article establishes a research model to analyze how group support factors, including peers’ support and family support, impact college students’ motivation to establish online business. College entrepreneurs need to consult their family members before starting a new career because of the power distance. Meanwhile, based on the collectivist cultural background, college students understand the importance of cooperation with peers’ group. Furthermore, influenced by uncertainty avoidance thinking, college entrepreneurs tend to rely on group supports, such as family funds and peers’ experiences, to reduce the probability of failure. Hence, this research designs uncertainty avoidance thinking as a moderating factor to explore its impact on the correlation between group support factors and college students’ online business motivation. To test the research model, it utilizes Chinese college students as samples and distributes online questionnaires to them. Through analyzing 458 samples based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the data analysis identifies that group support can positively affect college students’ online business motivation. The uncertainty avoidance factor also positively moderates the correlation between family support and college students’ online business motivation. To assist these students in establishing confidence in the online business, the Entrepreneurship Centre should pay much attention to the impact of peers’ support and family support.
This article establishes a research model to analyze how group support factors, including peers’ support and family support, impact college students’ motivation to establish online business. College entrepreneurs need to consult their family members before starting a new career because of the power distance. Meanwhile, based on the collectivist cultural background, college students understand the importance of cooperation with peers’ group. Furthermore, influenced by uncertainty avoidance thinking, college entrepreneurs tend to rely on group supports, such as family funds and peers’ experiences, to reduce the probability of failure. Hence, this research designs uncertainty avoidance thinking as a moderating factor to explore its impact on the correlation between group support factors and college students’ online business motivation. To test the research model, it utilizes Chinese college students as samples and distributes online questionnaires to them. Through analyzing 458 samples based on the partial least squares path modelling and variance-based structural equation modelling (PLS-SEM), the data analysis identifies that group support can positively affect college students’ online business motivation. The uncertainty avoidance factor also positively moderates the correlation between family support and college students’ online business motivation. To assist these students in establishing confidence in the online business, the Entrepreneurship Centre should pay much attention to the impact of peers’ support and family support.
An Optimal Proportion for Independent Directors in the Boardroom: An Empirical Study
Business Perspectives and Research, Ahead of Print.
The purpose of the article is threefold: (a) to analyze the causality between board independence and performance of the firm, (b) to examine the impact of board independence on financial performance, and (c) to ascertain whether the legislation of at least 50% of independent directors (IDs) influences the performance of the firm. We have employed a panel data framework for a sample of 442 Indian companies from 2013 to 2019. The estimation analysis has been conducted using panel Granger causality test, fixed effects method, and system generalized methods of moments. We further test whether the relationship differs across two categories of companies: one having IDs up to 50% and more; and second, the proportion is less than 50%. The results of our dynamic panel data analysis indicate that the ratio of IDs is found to have a positive association with the firm performance. Further, we found that firms with more than 50% IDs have a significantly higher firm performance than firms having less than 50% IDs. There should be an adequate ratio of independent members on board to avail benefits from their independent judgments without intervention in the ordinary course of business. It could be used as a preliminary study by the policymakers and regulatory authorities to set additional standards for the number and proportion of IDs.
The purpose of the article is threefold: (a) to analyze the causality between board independence and performance of the firm, (b) to examine the impact of board independence on financial performance, and (c) to ascertain whether the legislation of at least 50% of independent directors (IDs) influences the performance of the firm. We have employed a panel data framework for a sample of 442 Indian companies from 2013 to 2019. The estimation analysis has been conducted using panel Granger causality test, fixed effects method, and system generalized methods of moments. We further test whether the relationship differs across two categories of companies: one having IDs up to 50% and more; and second, the proportion is less than 50%. The results of our dynamic panel data analysis indicate that the ratio of IDs is found to have a positive association with the firm performance. Further, we found that firms with more than 50% IDs have a significantly higher firm performance than firms having less than 50% IDs. There should be an adequate ratio of independent members on board to avail benefits from their independent judgments without intervention in the ordinary course of business. It could be used as a preliminary study by the policymakers and regulatory authorities to set additional standards for the number and proportion of IDs.
Endogeneity and the Dynamics of Corporate Governance and Innovation in India’s Manufacturing Sector
Business Perspectives and Research, Ahead of Print.
This article presents the System Generalized Method of Moments (SGMM) results on the empirical association between innovation and corporate governance for a panel data set of 88 manufacturing companies in India listed on the NSE 200 Index from 2014 to 2020. GMM approach controls the potential sources of endogeneity inherent in the innovation—corporate governance relationship which mainly arises due to unobserved heterogeneity and simultaneity bias. We empirically analyze corporate governance and innovation to understand the market value of research and development practices of manufacturing companies in India. Our results indicate that Board size, Board meetings, and CEO duality support the “value creation” hypothesis of corporate governance of manufacturing companies in India. However, ownership concentration and Board meeting contradict “value creation hypotheses.” Therefore, this study identifies various factors of corporate governance that can help manufacturing companies in India in innovation and growth options. Further, this study recommends that ownership concentration and Board meetings should be properly assessed, as the concentrated owners should not merely act as expropriates, but rather should enable the long-term sustainability of the firm by taking the initiative, which enhances growth.
This article presents the System Generalized Method of Moments (SGMM) results on the empirical association between innovation and corporate governance for a panel data set of 88 manufacturing companies in India listed on the NSE 200 Index from 2014 to 2020. GMM approach controls the potential sources of endogeneity inherent in the innovation—corporate governance relationship which mainly arises due to unobserved heterogeneity and simultaneity bias. We empirically analyze corporate governance and innovation to understand the market value of research and development practices of manufacturing companies in India. Our results indicate that Board size, Board meetings, and CEO duality support the “value creation” hypothesis of corporate governance of manufacturing companies in India. However, ownership concentration and Board meeting contradict “value creation hypotheses.” Therefore, this study identifies various factors of corporate governance that can help manufacturing companies in India in innovation and growth options. Further, this study recommends that ownership concentration and Board meetings should be properly assessed, as the concentrated owners should not merely act as expropriates, but rather should enable the long-term sustainability of the firm by taking the initiative, which enhances growth.
Stock Market Prediction, COVID Pandemic, and Neural Networks: An Levenberg Marquardt Algorithm Application
Business Perspectives and Research, Ahead of Print.
Stock market forecasting has always piqued the interest of a wide range of investors, practitioners, and researchers. Stock prediction is a complex process due to the presence of an inherent noisy and volatile environment. The stock market’s movement is influenced by a variety of factors. The study of ANN models began in 1969, “when Minsky and Papert discovered two critical flaws in the Artificial Neural Network technique. The first was the machine’s ability to solve complex problems, and the second was the computers’ inability to run large ANN models efficiently”. The study aims to forecast the Nifty 50 using macroeconomic factors as input variables in the two sub-periods, that is, pre-COVID (February 2018–February 2020) and during COVID (March 2020–December 2021). A model trained using the LM algorithm was used for predicting the NSE’s flagship index Nifty 50. The findings reveal that the LM algorithm achieved 95.18% accuracy in predicting the Nifty 50 in the pre-COVID scenario. Whereas during COVID period, the proposed ANN model achieved 94.21% accuracy. The empirical results have important implications for every class of investors, such as FIIs, DIIs, retail investors, and so on.
Stock market forecasting has always piqued the interest of a wide range of investors, practitioners, and researchers. Stock prediction is a complex process due to the presence of an inherent noisy and volatile environment. The stock market’s movement is influenced by a variety of factors. The study of ANN models began in 1969, “when Minsky and Papert discovered two critical flaws in the Artificial Neural Network technique. The first was the machine’s ability to solve complex problems, and the second was the computers’ inability to run large ANN models efficiently”. The study aims to forecast the Nifty 50 using macroeconomic factors as input variables in the two sub-periods, that is, pre-COVID (February 2018–February 2020) and during COVID (March 2020–December 2021). A model trained using the LM algorithm was used for predicting the NSE’s flagship index Nifty 50. The findings reveal that the LM algorithm achieved 95.18% accuracy in predicting the Nifty 50 in the pre-COVID scenario. Whereas during COVID period, the proposed ANN model achieved 94.21% accuracy. The empirical results have important implications for every class of investors, such as FIIs, DIIs, retail investors, and so on.