Purushottam Bung | R .V .Institute of Management (original) (raw)

Papers by Purushottam Bung

Harnessing AI, Machine Learning, and IoT for Intelligent Business , 2024

The digital payment sector is becoming an increasingly important aspect of people’s life as a res... more The digital payment sector is becoming an increasingly important aspect of people’s life as a result of recent advancements in mobile and internet technology, delivering numerous fascinating and helpful services like M-banking. The m-banking system enables consumers to make purchases from anywhere using any electronic device, including mobile phones or tablets. M-banking is expected to have a better future as a result of current movements in international digital markets. The Reserve Bank of India said that the number of mobile banking transactions in India increased by 123% between 2018 and 2019, reaching 1.31 billion in total. More than 60% of Indian internet users use financial services via their mobile devices, according to Boston Consulting Group and Google, and the country’s mobile banking market is predicted to reach $1 trillion by 2023. Yet, these channels are more susceptible to various security risks when it comes to storing or transmitting information. Because there are so many various sorts of hazards, users are reluctant to use these services online. One of the aims of current research is to measure how perceived risk affects mobile banking in terms of intension and usage. The study also uses ML techniques to investigate the impact of other dimensions and measures, such as quality, ethics, simplicity, and demographic factors on m-banking patronage. The data is collected for the study using a structured questionnaire. The information gathered for the study was used to train and test ML models. Data collected were analyzed using various techniques, they are descriptive statistics, correlation and regression, principal component analysis, ML techniques, and other statistical techniques are used, to identify the key dimensions that impact customers’ desire to adapt and utilize m-banking. Research findings may assist in suggesting ways to mitigate m-banking risks prevalent among users, and highlight key factors that drive the user’s intention of usage. Institute can use the study outcomes to improve user access for sustainable growth.

Emerging Markets Case Studies, 2024

Learning outcomes After completion of the case study, students will be able to discuss the charac... more Learning outcomes
After completion of the case study, students will be able to discuss the characteristics of sustainable enterprises driving the innovation; analyze the concept of waste to wealth, along with its associated benefits and challenges; provide an example of a sustainable start-up that operates conventionally and is attempting to increase production capacity through automation; and describe the strategies for scaling up the business.

Case overview/synopsis
Mr Manigandan Kumarappan’s goal was to provide the world with alternatives to plastic and other nonbiodegradable articles used in homes, offices, hotels and other places which compelled him to leave his corporate life behind and become an entrepreneur. His knowledge, expertise and creativity made him work toward providing a sustainable solution to the plastic-free world which made him create leafy straws for the world. His start-up Evalogia made 10,000 straws a day, mostly with manual production and machine-assisted in part of the processes. Evalogia got orders from all over the world after the ban on plastic from many countries. However, Evalogia was unable to meet the demand, as the manufacturing process mostly depended on manual production at present. Hence, the company planned to scale up its production capacity from 10,000 straws per day to 100,000 straws to meet the demand through automation or by increasing the production units to meet the growing demand from domestic and international markets. Kumarappan wondered if increasing the number of manufacturing facilities would make it harder to hire new staff, manage existing ones, train them and provide overall supervision; if these tasks were not completed well, the product’s quality and, subsequently, its demand, might suffer. The automation process required huge investment, time and a great deal of skepticism for its success. Kumarappan was stuck over whether to add more production units or automate the process to increase production.

Zenodo (CERN European Organization for Nuclear Research), Sep 30, 2012

Zenodo (CERN European Organization for Nuclear Research), Jun 30, 2019

Social Science Research Network, Dec 31, 2022

Zenodo (CERN European Organization for Nuclear Research), Dec 29, 2012

International journal of research in finance and management, 2024

Anticipating Future Business Trends: Navigating Artificial Intelligence Innovations, 2024

This study presents a thorough investigation of the variables affecting price changes in the Indi... more This study presents a thorough investigation of the variables affecting price changes in the Indian Stock Market. The study aims to pinpoint the key elements that significantly influence the closing price of the Indian stock market (Nifty 50) by utilizing three different datasets and two different machine learning algorithms. The results show a notable result: the efficiency of the algorithm did not significantly increase as a result of including economic variables in the analysis. Instead, adding these variables reduced the algorithm's capacity for prediction. As a result, the study contends that technical factors, including historical price patterns, trading volumes, and technical indicators, have a greater impact on the trend prediction of the Indian Stock Market. For investors and other market participants looking to predict future market conditions, the implications of this study are extremely important. Investors can make well-informed investment decisions that could result in higher returns while lowering risks by realizing the predictive value of technical variables. This study emphasizes how crucial it is to combine machine learning algorithms with sophisticated data analysis methods to uncover patterns and insights from market data. Investors can improve their ability to predict market trends and make better investment decisions by incorporating technical variables into predictive models. The study adds to the knowledge by highlighting the necessity of focusing on technical aspects rather than just economic data when forecasting trends in the Indian Stock Market. It implies that the market's supply and demand dynamics, investor attitude, and trading patterns are better reflected when technical factors are taken into consideration. This study highlights the potential advantages of making investment decisions, portfolio allocations, and trading choices proactively based on expected market fluctuations. Overall, the study provides insightful information that might improve the performance and accuracy of forecasting models about the Indian Stock Market.

Migration letters, Dec 2, 2023

Journal of Informatics Education and Research, 2024

The principal aims of the research were to evaluate the impact of government regulat... more The principal aims of the research were to evaluate the impact of government regulations and Self Efficacy as a moderator on the development of social entrepreneurship. 459 respondents from Delhi-NCR filled out the questionnaire correctly that collected the data for further analysis. The technique employed in this study to gather information from a sample of 459 respondents was purposeful sampling. The three main methods for evaluating a research tool are validity and reliability testing, multiple linear regression testing, and hypothesis testing, which includes the t-test, F-test, and coefficient of determination tests. The results demonstrated that the two most significant variables impacting the development of social entrepreneurship are emotional intelligence and social innovation.

Educational Administration: Theory and Practice, 2024

The integration of IoT with digital marketing presents a myriad of opportunities for businesses t... more The integration of IoT with digital marketing presents a myriad of opportunities for businesses to enhance customer engagement, personalize marketing campaigns, and drive innovation. However, along with these opportunities come several inherent issues and challenges that businesses must address to maximize the benefits of IoT-enabled marketing strategies. Extracting actionable insights from this data requires sophisticated analytics tools and capabilities, as well as skilled data analysts who can interpret the data effectively. Ensuring data privacy and security is paramount, as IoT devices collect sensitive information about individuals and organizations, raising concerns about unauthorized access, data breaches, and regulatory compliance. Interoperability and integration issues also pose significant challenges for businesses seeking to leverage IoT for marketing purposes. IoT ecosystems often comprise diverse devices and platforms that may lack compatibility, making it difficult to integrate data and insights from different sources. Achieving seamless communication and collaboration between various IoT devices and marketing systems requires robust integration strategies and technical expertise. Moreover, consumer resistance and adoption barriers present obstacles to the widespread adoption of IoT-enabled marketing solutions. Some consumers may be hesitant to embrace IoT technologies due to concerns about privacy, security, and the perceived intrusiveness of targeted marketing tactics. Marketers must address these concerns transparently and ethically, demonstrating the value proposition of IoT-enabled services while respecting consumer preferences and rights.

Migration Letters, 2023

This study seeks to ascertain the principal elements influencing the application of Artificial in... more This study seeks to ascertain the principal elements influencing the application of Artificial intelligence (AI) and how the application of AI affects supply chain management (SCM) performance. During the industrial development period, the use of new technologies in supply chain management is important. A more thorough analysis of the problems with supply chain, AI implementation will offer a more unbiased viewpoint on the difficulties and advantages of integrating AI into SMEs' supply chain management. To achieve the research objectives, representative factors for variables were identified and the acceptability of the study sample was evaluated utilizing the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphere city. Regression Analysis was used to test the proposed hypotheses and to validate the conceptual model. The results indicated that the Managerial Support (MS), Competitive Pressure (CP), Government Support (GS), Vendor Partnership (VP), Compatibility (COMPA), and Relative Advantage (RA) factors are essential in AI implementation. The beta values of all the factors, as indicated by the coefficient, are 0.939 1 , 0.367, 0.240, 0.249, 0.190, and 0.161 respectively, which is a reasonable representation of their influence on SCM Performance (SCMP) and AI Implementation (AIIM). The study findings show that variables influence the decision to implement AI applications in supply chain management. Examining these variables is anticipated to have a positive impact and assist strategic planners in developing plans to use AI to support the operational requirements of the company both now and in the future. Research findings have aided companies in realizing the value of artificial intelligence, developing strategies and plans to swiftly transition to digital technology, and streamlining workflows to improve supply chain efficiency.

International Journal of Research in Finance and Management, 2024

Prediction of exchange rates is an important task of traders and practitioners in the recent fina... more Prediction of exchange rates is an important task of traders and practitioners in the recent financial markets era. Many statistical and econometric models are used in the time series analysis and prediction of foreign exchange rates. This study investigates the behavior of weekly exchange rates of the Indian rupee (INR) against the US dollar (USD) using time series analysis. This study used the SARIMA model in forecasting the INR/USD by aggregating seasonal data patterns in the foreign exchange market. Weekly RBI reference exchange rates from June 2013 to June 2023 were considered for the analysis. Finally, a forecast for ninety days was calculated which showed a depreciation of the Indian rupee against the US Dollar. The study found that the SARIMA model can be a better forecasting ability in advance of the prediction of currency exchange rates and momentum in the currency market.

Journal of Informatics Education and Research, 2023

A study on factors influencing workplace happiness and its relationship with job satisfaction, em... more A study on factors influencing workplace happiness and its relationship with job satisfaction, employee retention and work performance. The data was collected through the completion of a questionnaire by five hundred employees. The technique employed in this study to gather information from a sample of 446 respondents was purposeful sampling. Among the methods of data analysis are the following: Multiple linear regression testing, validity and reliability testing, and hypothesis testing, like t-test, F-test and coefficient of determination tests, are the three main methods of testing a research instrument. The research verdict shows that workplace happiness is the most job satisfaction factor (R square = 0.863; beta coefficient = 0.929) that influence the most on work performance (R square = 0.824; beta coefficient = 0.908) among employees. The study outlines the present state of contentment among management professionals and the relationship between contentment and production. When people feel content at work, they are more motivated, engaged, and productive. It is anticipated that this research would raise components of job satisfaction and employee perceptions of organizational support, which will help the company make its people happier at work.

International journal of management and development studies, Mar 15, 2015

India is the largest producer of mango in the world, contributing to nearly 46% of the total worl... more India is the largest producer of mango in the world, contributing to nearly 46% of the total world production. India has an edge over other countries when it comes to mango production in terms of natural resources required and climatic conditions. Despite all this mango cultivators of India are facing grave challenges including; very small land holdings, non availability of quality seedlings / saplings, huge post harvest loss due to dearth of infrastructure, middle men menace, lack of support by the concerned nodal bodies, lack of cooperative effort, poor profitability of the cultivation activity, etc., leading to negative growth rate (-0.86%). This has catalyzed the research work in this area. Major reasons for ill growth of this sector include: non availability of right varieties of mangoes that are ideal for processing; lack of necessary infrastructure; lack of cooperative effort amongst farming community; and lack of integration of all the activities starting from farm gate till final consumers because of ill functioning of the government departments/nodal bodies/institutions with no clear direction and goals. A coordinated, integrated and strategic effort of all the stake holders is must to turnaround this industry. Mango cultivation Industry of India has to undergo a radical shift to address all the above constraints and reap the enormous advantages/benefits/ profits which this sector is to offer. Problems / constraints have to be studied in wholesome, integrated and strategic manner rather than adopting piecemeal approach. Key words Mango cultivators, challenges, solutions, India

Social Science Research Network, Nov 12, 2013

Journal of advances in business management, Aug 20, 2015

Traditionally mentoring in higher education institutions was an informal one-to-one program where... more Traditionally mentoring in higher education institutions was an informal one-to-one program where graduate students as well as junior/ fresh faculty are matched with experienced faculty and put under them for influencing and fostering the intellectual development amongst students and career aspirations amongst junior faculty respectively. While such informal one-to-one programs help the students and junior faculty but fail to create a collaborative atmosphere in higher education institutions. Alternative mentoring techniques/methods/processes like; group mentoring, mentoring circles (Just like quality circles), and network mentoring can be employed which will help in creating collaborative atmosphere in higher education settings wherein all the parties involved, i.e. mentor, mentee and institution derive benefit. The concept of the collaborative models of mentoring shifts the focus of mentoring from the top-down approach of institutions assigning mentors to mentees to a more independent approach with the focus on mentee. Mentees develop their own relationship networks in relation to their particular needs. Earlier notion of one to one mentor relationship (Dyadic model) being superior to a network of many developmental mentoring relationships has been proved wrong. There are many advantages of mentoring circles/group mentoring/network mentoring. Individuals gain access to networks, reduction in feelings of isolation, greater connectivity, increased confidence and commitment, career progression, knowledge acquisition, and better understanding of the culture. In spite of all the advantages (Mentioned above) associated with collaborative mentoring models, such as mentoring circle or network mentoring or group mentoring, the implementation of these models compared to traditional one-to-one model (Dyadic model) of mentoring is very rare. The critical success factors in implementing these innovative collaborative models include; a commitment from all the parties involved, mutual trust, confidentiality, rapport amongst circle or network members and voluntary attendance. It should be seen as one of the many developmental activities undertaken to strengthen higher education.

International journal of business, Nov 30, 2017

India ranks second in the world (production of 45.91 mmt), next only to China (production of 72 m... more India ranks second in the world (production of 45.91 mmt), next only to China (production of 72 mmt), when it comes to fruit production. India contributes 9.54% of the total fruit production of the world. In spite of the India’s strong hold on the production of fruits it is alarming to know that India processes just 2% of the total fruit production with an alarming loss of around 35%. Only 20% of the production of processed fruits is being exported. India’s share of global exports of fresh fruits and processed fruit products is quite meager when we compare the same with other major fruit producers of the world, i.e., China, Brazil, USA, Italy, Spain, Mexico, Iran, Philippines, Turkey and Thailand (in the same order). The imports and exports analysis of this particular industry in India has been made using secondary data that was available. This data is then analyzed to know the per cent contribution of each fruit and each processed fruit product towards total imports and exports and CGR of the imports and exports of the same. The effort was made to know the causes for the particular pattern of imports and exports along with recommendations on policy front to elevate Indian fruit processing industry to international standards. A coordinated, integrated and strategic effort of all the stake holders, i.e., fruit growers, fruit processors, channel members, nodal bodies (Governmental and Non Governmental), and end users is must to turnaround this industry. Fruit Processing Industry of India has to undergo a radical shift to address all the constraints and reap the enormous advantages/benefits/profits which this sector is to offer and be the world’s largest fruit processing factory. Problems/constraints have to be studied in wholesome, integrated and strategic manner rather than adopting piecemeal approach.

Harnessing AI, Machine Learning, and IoT for Intelligent Business , 2024

The digital payment sector is becoming an increasingly important aspect of people’s life as a res... more The digital payment sector is becoming an increasingly important aspect of people’s life as a result of recent advancements in mobile and internet technology, delivering numerous fascinating and helpful services like M-banking. The m-banking system enables consumers to make purchases from anywhere using any electronic device, including mobile phones or tablets. M-banking is expected to have a better future as a result of current movements in international digital markets. The Reserve Bank of India said that the number of mobile banking transactions in India increased by 123% between 2018 and 2019, reaching 1.31 billion in total. More than 60% of Indian internet users use financial services via their mobile devices, according to Boston Consulting Group and Google, and the country’s mobile banking market is predicted to reach $1 trillion by 2023. Yet, these channels are more susceptible to various security risks when it comes to storing or transmitting information. Because there are so many various sorts of hazards, users are reluctant to use these services online. One of the aims of current research is to measure how perceived risk affects mobile banking in terms of intension and usage. The study also uses ML techniques to investigate the impact of other dimensions and measures, such as quality, ethics, simplicity, and demographic factors on m-banking patronage. The data is collected for the study using a structured questionnaire. The information gathered for the study was used to train and test ML models. Data collected were analyzed using various techniques, they are descriptive statistics, correlation and regression, principal component analysis, ML techniques, and other statistical techniques are used, to identify the key dimensions that impact customers’ desire to adapt and utilize m-banking. Research findings may assist in suggesting ways to mitigate m-banking risks prevalent among users, and highlight key factors that drive the user’s intention of usage. Institute can use the study outcomes to improve user access for sustainable growth.

Emerging Markets Case Studies, 2024

Learning outcomes After completion of the case study, students will be able to discuss the charac... more Learning outcomes
After completion of the case study, students will be able to discuss the characteristics of sustainable enterprises driving the innovation; analyze the concept of waste to wealth, along with its associated benefits and challenges; provide an example of a sustainable start-up that operates conventionally and is attempting to increase production capacity through automation; and describe the strategies for scaling up the business.

Case overview/synopsis
Mr Manigandan Kumarappan’s goal was to provide the world with alternatives to plastic and other nonbiodegradable articles used in homes, offices, hotels and other places which compelled him to leave his corporate life behind and become an entrepreneur. His knowledge, expertise and creativity made him work toward providing a sustainable solution to the plastic-free world which made him create leafy straws for the world. His start-up Evalogia made 10,000 straws a day, mostly with manual production and machine-assisted in part of the processes. Evalogia got orders from all over the world after the ban on plastic from many countries. However, Evalogia was unable to meet the demand, as the manufacturing process mostly depended on manual production at present. Hence, the company planned to scale up its production capacity from 10,000 straws per day to 100,000 straws to meet the demand through automation or by increasing the production units to meet the growing demand from domestic and international markets. Kumarappan wondered if increasing the number of manufacturing facilities would make it harder to hire new staff, manage existing ones, train them and provide overall supervision; if these tasks were not completed well, the product’s quality and, subsequently, its demand, might suffer. The automation process required huge investment, time and a great deal of skepticism for its success. Kumarappan was stuck over whether to add more production units or automate the process to increase production.

Zenodo (CERN European Organization for Nuclear Research), Sep 30, 2012

Zenodo (CERN European Organization for Nuclear Research), Jun 30, 2019

Social Science Research Network, Dec 31, 2022

Zenodo (CERN European Organization for Nuclear Research), Dec 29, 2012

International journal of research in finance and management, 2024

Anticipating Future Business Trends: Navigating Artificial Intelligence Innovations, 2024

This study presents a thorough investigation of the variables affecting price changes in the Indi... more This study presents a thorough investigation of the variables affecting price changes in the Indian Stock Market. The study aims to pinpoint the key elements that significantly influence the closing price of the Indian stock market (Nifty 50) by utilizing three different datasets and two different machine learning algorithms. The results show a notable result: the efficiency of the algorithm did not significantly increase as a result of including economic variables in the analysis. Instead, adding these variables reduced the algorithm's capacity for prediction. As a result, the study contends that technical factors, including historical price patterns, trading volumes, and technical indicators, have a greater impact on the trend prediction of the Indian Stock Market. For investors and other market participants looking to predict future market conditions, the implications of this study are extremely important. Investors can make well-informed investment decisions that could result in higher returns while lowering risks by realizing the predictive value of technical variables. This study emphasizes how crucial it is to combine machine learning algorithms with sophisticated data analysis methods to uncover patterns and insights from market data. Investors can improve their ability to predict market trends and make better investment decisions by incorporating technical variables into predictive models. The study adds to the knowledge by highlighting the necessity of focusing on technical aspects rather than just economic data when forecasting trends in the Indian Stock Market. It implies that the market's supply and demand dynamics, investor attitude, and trading patterns are better reflected when technical factors are taken into consideration. This study highlights the potential advantages of making investment decisions, portfolio allocations, and trading choices proactively based on expected market fluctuations. Overall, the study provides insightful information that might improve the performance and accuracy of forecasting models about the Indian Stock Market.

Migration letters, Dec 2, 2023

Journal of Informatics Education and Research, 2024

The principal aims of the research were to evaluate the impact of government regulat... more The principal aims of the research were to evaluate the impact of government regulations and Self Efficacy as a moderator on the development of social entrepreneurship. 459 respondents from Delhi-NCR filled out the questionnaire correctly that collected the data for further analysis. The technique employed in this study to gather information from a sample of 459 respondents was purposeful sampling. The three main methods for evaluating a research tool are validity and reliability testing, multiple linear regression testing, and hypothesis testing, which includes the t-test, F-test, and coefficient of determination tests. The results demonstrated that the two most significant variables impacting the development of social entrepreneurship are emotional intelligence and social innovation.

Educational Administration: Theory and Practice, 2024

The integration of IoT with digital marketing presents a myriad of opportunities for businesses t... more The integration of IoT with digital marketing presents a myriad of opportunities for businesses to enhance customer engagement, personalize marketing campaigns, and drive innovation. However, along with these opportunities come several inherent issues and challenges that businesses must address to maximize the benefits of IoT-enabled marketing strategies. Extracting actionable insights from this data requires sophisticated analytics tools and capabilities, as well as skilled data analysts who can interpret the data effectively. Ensuring data privacy and security is paramount, as IoT devices collect sensitive information about individuals and organizations, raising concerns about unauthorized access, data breaches, and regulatory compliance. Interoperability and integration issues also pose significant challenges for businesses seeking to leverage IoT for marketing purposes. IoT ecosystems often comprise diverse devices and platforms that may lack compatibility, making it difficult to integrate data and insights from different sources. Achieving seamless communication and collaboration between various IoT devices and marketing systems requires robust integration strategies and technical expertise. Moreover, consumer resistance and adoption barriers present obstacles to the widespread adoption of IoT-enabled marketing solutions. Some consumers may be hesitant to embrace IoT technologies due to concerns about privacy, security, and the perceived intrusiveness of targeted marketing tactics. Marketers must address these concerns transparently and ethically, demonstrating the value proposition of IoT-enabled services while respecting consumer preferences and rights.

Migration Letters, 2023

This study seeks to ascertain the principal elements influencing the application of Artificial in... more This study seeks to ascertain the principal elements influencing the application of Artificial intelligence (AI) and how the application of AI affects supply chain management (SCM) performance. During the industrial development period, the use of new technologies in supply chain management is important. A more thorough analysis of the problems with supply chain, AI implementation will offer a more unbiased viewpoint on the difficulties and advantages of integrating AI into SMEs' supply chain management. To achieve the research objectives, representative factors for variables were identified and the acceptability of the study sample was evaluated utilizing the Kaiser-Meyer-Olkin (KMO) measure of sampling adequacy and Bartlett's test of sphere city. Regression Analysis was used to test the proposed hypotheses and to validate the conceptual model. The results indicated that the Managerial Support (MS), Competitive Pressure (CP), Government Support (GS), Vendor Partnership (VP), Compatibility (COMPA), and Relative Advantage (RA) factors are essential in AI implementation. The beta values of all the factors, as indicated by the coefficient, are 0.939 1 , 0.367, 0.240, 0.249, 0.190, and 0.161 respectively, which is a reasonable representation of their influence on SCM Performance (SCMP) and AI Implementation (AIIM). The study findings show that variables influence the decision to implement AI applications in supply chain management. Examining these variables is anticipated to have a positive impact and assist strategic planners in developing plans to use AI to support the operational requirements of the company both now and in the future. Research findings have aided companies in realizing the value of artificial intelligence, developing strategies and plans to swiftly transition to digital technology, and streamlining workflows to improve supply chain efficiency.

International Journal of Research in Finance and Management, 2024

Prediction of exchange rates is an important task of traders and practitioners in the recent fina... more Prediction of exchange rates is an important task of traders and practitioners in the recent financial markets era. Many statistical and econometric models are used in the time series analysis and prediction of foreign exchange rates. This study investigates the behavior of weekly exchange rates of the Indian rupee (INR) against the US dollar (USD) using time series analysis. This study used the SARIMA model in forecasting the INR/USD by aggregating seasonal data patterns in the foreign exchange market. Weekly RBI reference exchange rates from June 2013 to June 2023 were considered for the analysis. Finally, a forecast for ninety days was calculated which showed a depreciation of the Indian rupee against the US Dollar. The study found that the SARIMA model can be a better forecasting ability in advance of the prediction of currency exchange rates and momentum in the currency market.

Journal of Informatics Education and Research, 2023

A study on factors influencing workplace happiness and its relationship with job satisfaction, em... more A study on factors influencing workplace happiness and its relationship with job satisfaction, employee retention and work performance. The data was collected through the completion of a questionnaire by five hundred employees. The technique employed in this study to gather information from a sample of 446 respondents was purposeful sampling. Among the methods of data analysis are the following: Multiple linear regression testing, validity and reliability testing, and hypothesis testing, like t-test, F-test and coefficient of determination tests, are the three main methods of testing a research instrument. The research verdict shows that workplace happiness is the most job satisfaction factor (R square = 0.863; beta coefficient = 0.929) that influence the most on work performance (R square = 0.824; beta coefficient = 0.908) among employees. The study outlines the present state of contentment among management professionals and the relationship between contentment and production. When people feel content at work, they are more motivated, engaged, and productive. It is anticipated that this research would raise components of job satisfaction and employee perceptions of organizational support, which will help the company make its people happier at work.

International journal of management and development studies, Mar 15, 2015

India is the largest producer of mango in the world, contributing to nearly 46% of the total worl... more India is the largest producer of mango in the world, contributing to nearly 46% of the total world production. India has an edge over other countries when it comes to mango production in terms of natural resources required and climatic conditions. Despite all this mango cultivators of India are facing grave challenges including; very small land holdings, non availability of quality seedlings / saplings, huge post harvest loss due to dearth of infrastructure, middle men menace, lack of support by the concerned nodal bodies, lack of cooperative effort, poor profitability of the cultivation activity, etc., leading to negative growth rate (-0.86%). This has catalyzed the research work in this area. Major reasons for ill growth of this sector include: non availability of right varieties of mangoes that are ideal for processing; lack of necessary infrastructure; lack of cooperative effort amongst farming community; and lack of integration of all the activities starting from farm gate till final consumers because of ill functioning of the government departments/nodal bodies/institutions with no clear direction and goals. A coordinated, integrated and strategic effort of all the stake holders is must to turnaround this industry. Mango cultivation Industry of India has to undergo a radical shift to address all the above constraints and reap the enormous advantages/benefits/ profits which this sector is to offer. Problems / constraints have to be studied in wholesome, integrated and strategic manner rather than adopting piecemeal approach. Key words Mango cultivators, challenges, solutions, India

Social Science Research Network, Nov 12, 2013

Journal of advances in business management, Aug 20, 2015

Traditionally mentoring in higher education institutions was an informal one-to-one program where... more Traditionally mentoring in higher education institutions was an informal one-to-one program where graduate students as well as junior/ fresh faculty are matched with experienced faculty and put under them for influencing and fostering the intellectual development amongst students and career aspirations amongst junior faculty respectively. While such informal one-to-one programs help the students and junior faculty but fail to create a collaborative atmosphere in higher education institutions. Alternative mentoring techniques/methods/processes like; group mentoring, mentoring circles (Just like quality circles), and network mentoring can be employed which will help in creating collaborative atmosphere in higher education settings wherein all the parties involved, i.e. mentor, mentee and institution derive benefit. The concept of the collaborative models of mentoring shifts the focus of mentoring from the top-down approach of institutions assigning mentors to mentees to a more independent approach with the focus on mentee. Mentees develop their own relationship networks in relation to their particular needs. Earlier notion of one to one mentor relationship (Dyadic model) being superior to a network of many developmental mentoring relationships has been proved wrong. There are many advantages of mentoring circles/group mentoring/network mentoring. Individuals gain access to networks, reduction in feelings of isolation, greater connectivity, increased confidence and commitment, career progression, knowledge acquisition, and better understanding of the culture. In spite of all the advantages (Mentioned above) associated with collaborative mentoring models, such as mentoring circle or network mentoring or group mentoring, the implementation of these models compared to traditional one-to-one model (Dyadic model) of mentoring is very rare. The critical success factors in implementing these innovative collaborative models include; a commitment from all the parties involved, mutual trust, confidentiality, rapport amongst circle or network members and voluntary attendance. It should be seen as one of the many developmental activities undertaken to strengthen higher education.

International journal of business, Nov 30, 2017

India ranks second in the world (production of 45.91 mmt), next only to China (production of 72 m... more India ranks second in the world (production of 45.91 mmt), next only to China (production of 72 mmt), when it comes to fruit production. India contributes 9.54% of the total fruit production of the world. In spite of the India’s strong hold on the production of fruits it is alarming to know that India processes just 2% of the total fruit production with an alarming loss of around 35%. Only 20% of the production of processed fruits is being exported. India’s share of global exports of fresh fruits and processed fruit products is quite meager when we compare the same with other major fruit producers of the world, i.e., China, Brazil, USA, Italy, Spain, Mexico, Iran, Philippines, Turkey and Thailand (in the same order). The imports and exports analysis of this particular industry in India has been made using secondary data that was available. This data is then analyzed to know the per cent contribution of each fruit and each processed fruit product towards total imports and exports and CGR of the imports and exports of the same. The effort was made to know the causes for the particular pattern of imports and exports along with recommendations on policy front to elevate Indian fruit processing industry to international standards. A coordinated, integrated and strategic effort of all the stake holders, i.e., fruit growers, fruit processors, channel members, nodal bodies (Governmental and Non Governmental), and end users is must to turnaround this industry. Fruit Processing Industry of India has to undergo a radical shift to address all the constraints and reap the enormous advantages/benefits/profits which this sector is to offer and be the world’s largest fruit processing factory. Problems/constraints have to be studied in wholesome, integrated and strategic manner rather than adopting piecemeal approach.

RVIM Journal of Management Research, 2019

RVIM Journal of Management Research, 2019

TATVA, 2012

Peter Bregman advises and consults to CEOs and their leadership teams in organizations ranging fr... more Peter Bregman advises and consults to CEOs and their leadership teams in organizations ranging from Fortune 500 companies to start-ups and nonprofits. He speaks worldwide on how people can lead, work and live more powerfully. He is a frequent guest on public radio, provides commentary for CNN and writes for Harvard Business Review, Fast Company, Forbes and Psychology Today. He lives in New York City. Review Goal setting, time management and task management have become the most sought after soft skills amongst executives/entrepreneurs of all cadres irrespective of their functional domain. The pressures on executives/entrepreneurs to achieve maximum in shortest span of time has become order of the day. There are so many books available on the above topic which tell about the importance of goal setting, time management, and task management and how one can manage these in an abstract manner like; classifying activities to be done or tasks to be and Neither Urgent nor Important and then allocating time and delegating work accordingly and so on. But Peter Bregman in this book has in fact explained what one has to do or can do to ensure the honing of above mentioned soft skills to achieve maximum in the shortest span of time. As the title says very clearly, one has to dedicate eighteen minutes out of four hundred eighty minutes of a working day as per the following; Five minutes before the start of the day: for setting specific targets for the day and planning.

Fortune Institute of International Business Review (FBR), 2015

Abstract M/s. R.N.Food products came into existence in November 1997. Starting with manufacturing... more Abstract
M/s. R.N.Food products came into existence in November 1997. Starting with manufacturing basic spice powders; the firm’s products were available throughout Karnataka and Goa. They were available in convenient pack sizes ranging from 50 grams to 10 Kgs. In the year 2002, R.N.Foods started manufacturing mixed spice powders like Garam masala, Chicken Masala and Sambar powder. In the year 2002, R.N.Foods added pickles to its portfolio producing according to FPO standards. Pickles were sold in two different brands, namely ‘P&P’ (premium brand) and ‘KrsnA’ (regular brand). The case outlines the way the entrepreneur started the business, the challenges he faced and what ultimately happened. It further looks into various risks and decisions that impact a small scale set-up.

Keywords
Entrepreneurship, Initiative, Small and Medium Enterprise, Business Strategy

Himalaya Publishing House Pvt. Ltd.,, 2014

An economy at large will thrive when all the major industries will perform to their fullest poten... more An economy at large will thrive when all the major industries will perform to their fullest potential. The industry will perform to its fullest capacity when each and every incumbent firm is aggressive enough to face the global competition. A detailed study on each and every industry is what is required today to understand the nuances of a particular industry. Fruit processing industry in general and mango processing industry in particular is one of the emerging industries of India which has a tremendous potential yet to be unleashed. There lies a huge potential which needs to be exploited and make India a world’s biggest fruit processing factory.
The book which is produced out of the Doctoral research work serves basically two purposes. One, it is a ready guide on Indian fruit processing industry in general and mango processing industry in particular giving complete picture of the industry and explaining the underlying forces that are shaping the competition in this particular industry. The attempt has been made to compare India vis-à-vis Brazil, a global leader in this space covering all the stake holders namely; Growers, Processors, Government, Nodal bodies, Middlemen, end Consumers, Cooperatives, Associations, etc. Second, it is a book based on total research with no theory which can be used by the policy makers, industry incumbents, entrepreneurs and research scholars.