Professor & Dean,
Office of Doctoral Studies, O.P. Jindal Global University, Sonipat,Haryana
Prof. (Dr.) Krishan K Pandey is currently working as a professor in the area of decision sciences at Jindal Global Business School (JGBS) and Dean, Office of Doctoral Studies (ODS) at O. P. Jindal Global University (JGU), Sonipat, Haryana. Dr. Pandey holds Bachler’s, Masters and Doctorate in Statistics from J.N.V. University, Jodhpur. He also holds a Master of Business Administration degree from Allahabad and an Executive Program degree in data science from Xavier School of Management (XLRI), Jamshedpur.
Before joining Jindal Global University, he has held faculty and Assistant Dean level positions at the University of Petroleum & Energy Studies (UPES), Dehradun, Banasthali University, Rajasthan, and J.N.V. University, Jodhpur. Dr. Pandey has worked for Fachhochschule Frankfurt Am Main University of Applied Sciences, Frankfurt, Germany on European Union’s project for capacity building of the Indian aviation sector.
He has several years of academic experience, both in the domain of teaching and research. His research interest includes Data Mining, Predictive Analytics, Energy and Environment, Business Analytics, Risk Analysis, Knowledge Management, Small Area Estimation, and Statistical Modeling.
Dr. Pandey published 50+ research papers in top-class academically reputed journals along with two (2) books and several book chapters from the area of his research interest. He has guided 16 Ph.D. scholars from across the industry and academia in different areas of his specialization. He is also working as an editorial board member and reviewer for various reputed journals having a high impact factor in the areas of Renewable energy and sustainable development. He has also successfully completed an international project in collaboration with Sheffield Hallam University, funded by the Global Challenges Research Fund (GCRF), England, U.K.
He has worked as Editor in Chief, for UPES Management Review- A bi-annual International Journal of Core Sector. He is also acting as an editorial board member and reviewer for various reputed journals having a high impact factor like Renewable and Sustainable Energy Reviews, Applied Energy, Energy Policy,Bioresource Technology, Journal of cleaner production (Elsevier), Environmental Technology (Taylor and Francis), International Journal of Logistics Management (Emerald), etc.
Dr. Pandey organized many international and national conferences as a convener and co-convener for imparting and sharing the research fundamentals at various platforms. He has conducted training sessions for executives from aviation and energy sectors- Oil India, IOCL, HPCL, BPCL, ONGC, GAIL, IBM, etc.,
Dr. Pandey received many awards & prizes for his meaningful contribution and dedication towards research and development, which includes an outstanding reviewer award, best paper awards, Exemplary work award, Most Devoted Teacher Award, Young Statistician Award, Exemplary Research Award, etc.
Office of Doctoral Studies, O.P. Jindal Global University, Sonipat,Haryana
Office of Doctoral Studies, O.P. Jindal Global University, Sonipat,Haryana
Jindal Global Business School, O.P. Jindal Global University, Sonipat,Haryana
University of Petroleum & Energy Studies (UPES) Dehradun
University of Petroleum & Energy Studies (UPES) Dehradun
University of Petroleum & Energy Studies (UPES) Dehradun
University of Petroleum & Energy Studies (UPES) Dehradun
Banasthali Vidhyapeeth University, Rajasthan
Alcobex Metals Limited India, Jodhpur,Rajasthan
Jai Narain Vyas University, Jodhpur, Rajasthan
SHUATS
Jai Naraian Vyas University, Jodhpur, Rajasthan
Jai Narain Vyas University, Jodhpur,Rajasthan
Xavier School of Management (XLRI), Jamshedpur
Indian Institute of Management, Raipur
Indian Institute of Management, Kolkata
Dr. Pandey’s research interests focus on a wide range of issues related to Energy and Environment, Energy Policy,Renewable Energy, Sustainable Development, Cyber-security,Data Mining& Business Analytics. He has published his work in the leading national and international journals likeApplied Energy, Renewable Energy, Energy Policy, Renewable and Sustainable Energy Reviews, Statistics in Transition, & Energy Systems. Dr. Pandey has worked for Fachhochschule Frankfurt Am Main University of Applied Sciences, Frankfurt, Germany on the European Union’s project for capacity building of the Indian aviation sector.
One of his recent articles empirically explores the connection between energy consumption, economic growth & CO2 emissions at the sectoral level. The article concludes thatIndian endeavor to curb CO2 emission should be sectoral electricity consumption specific rather thanbeing generic. India should frame measures that boost sustainable development taking into consideration sectoral specific carbon-related issues.
In another co-authored article, he argued about cybersecurity needs in the Indian power sector. Inadequate security planning in designing Smart Grids can potentially putthe country's power sector stability at peril. He also identified important cybersecurity threats across the value chain of the energy sector, and suggested cybersecurity regulations based on the experience of regulators in Indian Banking and Telecom sectors and power sector worldwide. Dr. Pandey, through his studies, identified manychallenges that India needs to address to attain sustainable development.
The atmospheric concentrations and world-wide emissions of CO2 continue to rise despite of increasing efforts of decarbonisation. Clearly, deployment of renewable energy will not be enough to reduce the carbon in the atmosphere. We cannot achieve climate objectives without Carbon Capture and Storage (CCS). Therefore, to take the first step toward CCS in India a detailed study needs to be conducted on feasibility of CCS in India. From the perspective of technological feasibility few research has quantified the potential of carbon capture in India and identified the geographical mapping of the potential. But a prior understanding of the major challenges needs to be the first step before going for detailed feasibility study. The study revisits the growth of CCS in global context and attempts to understand India’s commitments on the same. The study further attempts to identify the challenges from the perspective of emitters in Indian context. The study includes both the oil and gas, and fossil fuel-based power generation plants so that the challenges common for both sectors may be considered before initial feasibility analysis. The study finds 6 categories of challenges namely Cost of CCS, Geo-storage capacity, Source sink matching, Supply Chain and building rate, Policy regulations and public acceptance. The study further establishes the relationship among the identified challenges by adopting Interpretive Structural Modelling (ISM) approach. The study identifies the priority areas for policy makers.
Artificial Intelligence (AI) biases are becoming prominent today with the widespread and extensive use of AI for autonomous decision-making systems. Bias in AI can exist in many ways- from age discrimination and recruiting inequality to racial prejudices and gender differentiation. These biases severely impact various levels, leading to discrimination and faulty decision-making. The research aims to systematically explore and investigate the pervasiveness of the AI bias impacts by collecting, analysing, and organizing these impacts into suitable categories for effective mitigation. An in-depth analysis is done using a systematic literature review process to gather and outline the variety of impacts discussed in the literature. Through our holistic qualitative analysis, the research reveals patterns in the types of bias impacts that can be categorized, from which a classification model is developed that places the impacts in 4 primary domains: fundamental rights, individuals and societies, the financial sector, and businesses and organizations. By identifying the impacts caused by AI bias and categorizing them using a systematic approach, a set of specific targeted mitigation strategies relative to the impact category can be identified and leveraged to assist in managing the risks of AI bias impacts. This study will benefit practitioners and automation engineers on a global scale who aim to develop transparent and inclusive AI systems..
Purpose: The low level of financial literacy among young adults is a pressing concern at both individual and country levels. Therefore, there is a dire need to understand the best-worst antecedents of financial literacy and how they influence each other.
Design/methodology/approach: A two-phased multicriteria decision-making (MCDM) technique consisting of best-worst method and interpretive structural modeling (BWM-ISM) was employed for pair-wise comparison, assigning weights, ranking and establishing the relationship among antecedents of financial literacy.
Findings: Results suggest that use of Internet (SF1), role of financial advisors (SF3) and education level of individuals (DS7) are top ranked antecedents, whereas masculinity/feminity, language and power distance in society are the least ranked antecedents of financial literacy. Findings will help both academicians and practitioners focus on the key factors and make efforts to increase financial literacy by minimizing resource usage.
Originality/value: The current study provides clarity among antecedents of financial literacy by following BWM-ISM approach for the first time in the financial literacy context.
Purpose: Circularity has acted as an essential phenomenon for small and medium enterprises (SMEs) in emerging economies, pressuring entrepreneurs to its adoption in their businesses. During the adoption and implementation of circularity, entrepreneurs or circular entrepreneurs (to be precise) are facing various challenges to its effective functioning. However, the scholarly literature has offered limited research into this phenomenon. Thus, the purpose of this research is to identify the various barriers and sub-barriers for circular entrepreneurs to adopt circularity in SMEs of emerging economies.
Design/methodology/approach: A combined qualitative and quantitative approach was employed to achieve the objectives of the study. In the first stage, through an extensive literature review, a list of barriers was identified and in the second stage, a deductive approach was employed to finalize the barriers. Finally, Best-Worst Method (BWM), a multi-criteria decision-making (MCDM) method, was used to analyse the significant importance of the barriers.
Findings: The findings of the study suggested the “financial barrier” as the first-ranked barrier in the adoption of Circular Business Models (CBMs), followed by the “regulatory and operational barrier” as the top second and third barriers. In terms of sub-barriers, “lack of access to funding and capital” has been identified as the top sub-barrier in the adoption of CBM, followed by “excessive regulations and red tape” and “challenges due to ambiguity of the concept”.
Practical implications: To transition from a circular to a linear business approach considerably quicker and smoother, entrepreneurs may utilize the findings of this study as a blueprint for the steps to overcome the barriers in a linear to a circular transition.
Originality/value: This research differentiates from other studies due to solicited input directly from the people who are most familiar with the challenges of making the transition from linear to CBM, i.e. the entrepreneurs themselves.
Energy from the ocean has been globally recognized as one of the most significant sources of renewable energy. In the Indian context, it has the potential to meet the country's long-term energy requirements as the Indian peninsula possesses a vast coastline. However, harnessing the energy from the ocean has several challenges and risks that serve as a major roadblock to India's attainment of this energy advantage. This study explores the challenges to ocean energy development by reviewing the literature and analyses the complex interactions between them using the Interpretive Structural Modelling approach. Data are collected from twenty-six experts and an interpretive model is developed. The analysis reveals that lack of policy push, technology, R&D, and trained workforce are some of the key barriers to the development of the ocean energy sector in India, requiring special focus to streamline the infrastructural development of ocean energy as a sustainable source. The findings provide valuable strategic insights to policymakers.
Background: The internet-based remote learning and pedagogical revolution in the era of the covid pandemic has contributed to the boom in video conferencing technologies and resulted in new phenomena of exhaustion and fatigue experienced during virtual meetings.
>Objective: To examine the psychometric properties of the Zoom Exhaustion and Fatigue Scale (ZEFS) in the Indian university student population and to explore its impact on mental health.
Method: Five hundred and seven students participated in this study and 484 completed the ZEFS and the Depression, Anxiety, and Stress Scale (DASS) via online survey. Psychometric validation of the ZEFS was performed with confirmatory factor analysis and reliability was assessed with Cronbach alpha and composite reliability. Pearson correlations were used to explore the relationship between the ZEFS and the DASS.
Results: The results showed excellent reliability of the full ZEFS scale with a high Cronbach alpha and composite reliability score (0.94). The validity of the ZEFS within the Indian student sample was supported with favorable fit indices (CFI = 0.968, GFI = 0.932, AGFI = 0.897, CMIN/DF = 3.198, RMSEA = 0.06) consistent with the original factor structure. The Depression, Anxiety, and Stress scales of the DASS were found to be significantly correlated with Zoom fatigue (p < .01).
Conclusion: Our data suggest that the Indian version of the ZEFS is a psychometrically sound measure to assess Zoom fatigue in the Indian student population.
Food waste has far-reaching effects on the global population and thus has been given significant attention in United Nations Sustainable Development Goals. An increased generation of food waste at the consumer level due to online food delivery (OFD) systems has been a topic of research attention. The present study empirically investigates the impact of vagueness in plate size information on OFD apps on the food waste behavior of consumers and potential underlying psychological mechanisms involved in the online food ordering process. Through a 2 × 2 experimental design carried out in India, the causal effect of the vagueness in plate size information on food waste is examined through the mediating roles of anticipated shortage and over-ordering. When consumers anticipate a food shortfall due to vagueness in plate size information, they prefer to order more than needed, which eventually leads to higher food waste (FW). The theoretical and practical implications of the study are discussed.
Background: The ingestion of various animals with psychoactive properties has been observed since antiquity. Though unusual, lizard use has been reported in the literature as case reports. Yet the rarity of this phenomenon has not been explored through large-scale studies. This paper systematically reviews available case reports of individuals using lizards for recreational purposes and synthesizes the evidence in terms of socio-demographic, clinical, and treatment variables.
Methods: We conducted a systematic review of the literature including original papers, case reports, case series, and letters to the editor on MEDLINE and Taylor & Francis database. The search terms used were lizard AND (addiction OR psychedelic OR psychoactive). Additionally, bibliographies of published cases were searched for an exhaustive review.
Results: Eight case reports (from seven publications) were included for qualitative synthesis. The sample consisted of all males (age = 28 ± 8.97). Findings revealed that the lizards were self-acquired and consumed through varied methods. Ingestion was reported usually as pleasure-inducing, though without any prominent withdrawal symptoms. Additionally, it was highly concurrent with other substances.
Introduction: The lockdown and stay at home orders implemented by the Indian government to inhibit the spread of COVID-19 disrupted the lifestyle of most individuals in the country. This appeared to result in behavioral changes such as increased internet usage, feelings of loneliness, and disturbance of sleeping patterns.
Objectives: The objective of the present study was to examine IGD prevalence and its association with loneliness and insomnia among the Indian population during the COVID-19 pandemic. Based on the previous literature, it was hypothesized that IGD would be positively associated with both loneliness and severity of insomnia. .
Materials and Methods: Utilizing a cross-sectional design, a total of 372 participants (54% males, 42.4% females; 3.5% other; mean age 23.26 years [SD=9.07]) completed an anonymous self-report survey. The three key variables were assessed using the Internet Gaming Disorder Scale-Short Form (IGDS9-SF), the UCLA Loneliness Scale (Version 3), and the Insomnia Severity Index (ISI). .
Results: The prevalence of IGD among Indians during the COVID-19 pandemic was 0.8% in the total sample and 2.02% among gamers. Regression analysis indicated that IGD was associated with average hours spent online gaming per day (β=0.164; p=0.02), loneliness (β=0.177; p=0.01), and severity of insomnia (β=0.483; p<0.001). .
Conclusion: The study indicated average hours spent online gaming, loneliness, and severity of insomnia as predictors of IGD. Future research is required to develop a comprehensive understanding of internet gaming behaviors during unprecedented times such as COVID-19.
Purpose : This paper is aimed at analyzing the inter-contextual relationships among the factors that led to inadequate management of electronic and electrical waste (WEEE) during COVID-19 using a subjective perspective.
Design/methodology/approach: Grey sets and a Decision-Making Trial and Evaluation Laboratory (DEMATEL)-based approach has been employed to identify the causal association of intertwined WEEE management barriers.
Findings: Results reveal the lack of implementation of the legislative framework, extended producer responsibility and lesser corporate initiatives are some of the most challenging WEEE management challenges during the current pandemic.
Practical implications: The findings of the study would enable stakeholders of WEEE management toward building resilient policies and effective implementation plans during as well as post-crisis situations.
Originality/value : COVID-19 led challenges related to healthcare waste have attracted a significant amount of scholarly attention, but there has been lesser attention toward e-waste management challenges during the pandemic. Negligence toward e-waste management can pose threats to the environment as well as human well-being.
Over the past decade, there has been a constant spotlight on introducing sustainability in the supply chain (SC). The materialistic human greed for production and consumption has led to a radically increased level of greenhouse gases. SC has become its principal contributor. We are addressing this socio-economic environmental challenge by developing a multi-stakeholder framework and focusing on a knowledge-based net zero supply chain, as there are no concrete existing studies that have investigated current state-of-the-art operations in this relevant field. Therefore, this research has been conducted to investigate the drivers, barriers and practices through which net zero economy (NZE) can be attained in a knowledge-based SC. In this regard, the paper conducts an exploratory systematic review of selected articles from peer-reviewed journals. The findings indicate that primary stakeholders (i.e. organisations and suppliers) require to take an active role in bringing about sustainable changes in practice. However, external perspectives (i.e. government, society, consumers and community) have also been identified as sources that create challenges as well as have the potential to aid sustainable industrial practices. Additionally, progress can be enhanced through proper policies, regulations and a knowledge-based conceptual framework to pave the way for a sustainable environment. Proper practices for NZE also provide scope for economic growth through cost-effective production. This paper will be beneficial for practitioners as well as policy makers on a global scale who aim to attain NZE for sustainability.
The outbreak of the novel Coronavirus pandemic has brought the world to a standstill. The constant increase in the rise of cases and deaths has compelled nearly all countries to impose lockdowns and other restrictive measures. The restrictions on travel and other non-essential activities have raised some serious business concerns for ridesharing, carpooling, and cab rental services. This study aims to identify, analyze, and prioritize the commuters’ barriers to Appbased Ridesharing Services during COVID-19’s first and second waves, and potential ways of adaptation for an anticipated third wave in Indian contexts. The hierarchy of barriers is established using the responses from sixty respondents and their analysis using the multi-criteria decision-making (MCDM) technique, the Analytic Hierarchy Process (AHP). ‘Safety from contagion’ was found to be the most significant and strong factor followed by the desire for personal space and personal security as the most important inhibitors for not choosing ridesharing services during COVID-19. Socio-economic status and the lack of reliability of service were not given much importance by the respondents. The current and potential implications for sustainable business and the environment are also discussed.
The outbreak of COVID-19 has caused psychological distress among the Indian population. There are several scales that assess fear and distress related to COVID-19 among individuals. However, these scales are context-specific and lack multi-cultural environment applicability in countries such as India. Therefore, the present study developed a psychometric instrument to assess psychological responses to COVID-19 among the Indian population. A total of 420 participants (60.5% females, Mage=25.89 years) were recruited online using a convenience sampling technique. The 16-item COVID-19 Psychological Distress Scale (CPDS16) was developed based on the extensive review of the existing scales on psychological constructs related to COVID-19 (yielding four scales with a total of 37 items) and independent review by two external experts. Internal consistency and reliability of the scale was established by using corrected item-total correlations, Cronbach’s alpha, and McDonald’s omega. Factor structure of the scale was determined by using exploratory factor analysis (EFA). Convergent validity of the scale was established by correlating CPDS-16 scores with the three subscales of the Depression, Anxiety, and Stress Scale (DASS-21). Corrected item-total correlations (range = 0.43 to 0.70), Cronbach’s alpha (α = 0.90), and McDonald’s omega (ω = 0.89) provided evidence for very good internal consistency and reliability of the scale. EFA of the CPDS-16 demonstrated a twofactor structure identified as ‘individual level distress’ (10 items) and ‘community level distress’ (6 items). Convergent validity of the scale was established using the DASS-21 with statistically significant and positive correlations between CPDS-16 and the three DASS-21 subscales (i.e., depression, anxiety, and stress). The CPDS16 is a reliable and valid instrument in assessing psychological distress caused due to COVID-19 with robust psychometric properties. The scale can be administered rapidly and is useful in screening psychological distress caused due to COVID-19.
Sharing of Do-It-Yourself (DIY) cooking outcomes on various social media platforms was one of the most visible phenomena on the digital landscapes during COVID-19 led lockdowns. Since the prosumption of food is not considered as a source of alternative food system only, but also as a source of pleasure, DIY-cooking-related social media posts during the lockdown were prevalent among internet users. This paper examines variations in the social media posting behavior of food prosumers based on four individual and three social factors of gender, age, marital status, and family structure. Responses from 198 Facebook food community members were used to test the statistical hypotheses. The analyses report that the need for entertainment value while posting on social media was different among different demographic factors, whereas self-discovery and social enhancement did not exhibit variations across demographics. The need for social presence mattered more for unmarried people during social isolation whereas females used DIY-cooking posting to fulfil the need for uniqueness. The implications for social sustainability and business practices are also discussed.
Purpose:Limited research efforts have been undertaken despite the pivotal role of employees' voluntary behaviours in the success of organizations' environmental sustainability programs. In this context, the present study examined the association between employee's mindfulness (EM) and voluntary pro-environmental behaviour (VPEB) at the workplace, and also the mediating effect of connectedness to nature (CNS) on this relationship.
Design/methodology/approach: Grounded in the re-perceiving theory, a model was developed with EM as an independent variable, CNS as the mediator and employees VPEB at the workplace as the dependent variable. Based on the online responses from 421 employees working in manufacturing as well as services sectors in India, analysis was undertaken by utilizing confirmatory factor analysis, Pearson correlation and the PROCESS macro of Hayes (2017).
Findings: EM was noted to be positively influencing employee's VPEB at the workplace, and the mediation analysis indicated that CNS partially intervenes in this relationship.
Practical implications:Corporate leaders striving to achieve the organization's environmental sustainability goals could strive to build a pro-environment culture at the workplace by developing employees' mindfulness and sense of CNS. As the findings have depicted, this would positively influence employee's VPEB at the workplace which in turn will help organizations in achieving their environmental sustainability goals.
Originality/value: This study is the first to examine how EM through CNS motivates employees to engage in VPEB, especially in the organizations' context. Moreover, the re-perceiving theory of mindfulness was also extended in the organizations' environmental sustainability context.
Purpose: This study aims to examine the relationship between employees’ mindfulness and pro-environmental behaviour, along with the mediating role of self-transcendent values, at the workplace.
Design/methodology/approach :The study uses online data collected from 381 respondents employed in different industries across India. Confirmatory factor analysis was used to check the construct’s validity and reliability and Pearson correlation was used to examine the relationship between the variables. Moreover, the PROCESS macro of Hayes (2017) was used to examine the mediation.
Findings : Employees’ mindfulness was found to be positively associated with voluntary pro-environmental behaviour at the workplace, and the mediation analysis specifies that a self-transcendent value partially mediates this relationship.
Research limitations/implications : This study tested and extends the S-ART model and Schwartz value theory in the context of employees’ pro-environment behaviours at the workplace.
Practical implications: The results could be encouraging and helpful for top management and organizational change champions in strategizing and effective implementation of mindfulness programmes that would encourage and enhance employees’ voluntary participation in environment-friendly activities at their workplace.
Originality/value :Despite the decisive role of employees in organisations’ environmental sustainability programmes’ success, the availability of scant literature has led researchers to call for more studies. The present study is timely and could be the first to examine the role of employees’ mindfulness and self-transcendent values in influencing employees’ engagement in environmental-friendly behaviours at the workplace.
This study explores the relationship between employees’ mindfulness and voluntary pro-environmental behaviour at the workplace, and also the mediating role of connectedness to nature. Based on 421 online survey responses, confirmatory factor analysis was conducted to establish the validity and reliability of the conceptualised model. Pearson correlation was undertaken to study the relationship between variables, and mediation was examined using the PROCESS macro of Hayes. Findings were encouraging and employee mindfulness was found to be positively influencing voluntary proenvironmental behaviour, and the mediation analysis indicated the intervening role of connectedness to nature in this relationship. This study could be the first to examine, how mindfulness through connectedness to nature motivates employees to engage in voluntarily pro-environmental behaviours. The findings could be of much interest to organizational change champions seeking to encourage employees to voluntarily participate in pro-environment behaviours
Electricity thefts in connivance with employees of electricity distribution companies, remain the Achille’s heel of power sector, addressing which continue to be the holy grail. The lackluster performance of technological measures to curb electricity thefts highlights the need to investigate the human aspectstoo. That’s what this study aims at. The findings, grounded in the responses of the nineteen employees of the Indian electricity distribution companies, detail the factors that induce employees to collude with consumers in electricity theft.
Electricity Supply Limited (SECL) has been the player involved both in generation and transmission of electricity. The study aims at forecasting annual electricity consumption of the company and suggest an optimal combination of renewable options namely wind, small hydro, solar photo voltaic, solar thermal and biomass to meet the RPO targets of subsequent 25 years. A linear regression model has been used for forecasting the consumption and RPO contributions whereas linear programming model has been used for determining the optimal combination of renewable sources under consideration over the segments of generation and short term power purchase agreements for meeting overall REC requirement from non-solar and solar sources. The study recommends for long term PPAs of 1 MW for wind, 30 MW of small hydro and 20MW of biomass instead of 1-year short term PPA and a need for promoting wind farms in the near future.
This study empirically investigates the impact of energy consumption (electricity consumption) and economic growth (in terms of real Gross Domestic Product) on the environmental degradation in form of CO2 emissions. The study aims to identify the interrelationship among the three variables viz. real GDP, electricity consumption & CO2 emissions. The analysis is based on the time series annual data for the period of 1971-2017. We tested the stationarity for the variables by applying Dicky Fuller test and examined the short run & long run causal relationships among electricity consumption, real GDP and CO2 emissions using Johansen Cointegration & Granger Causality approach. The Johansen cointegration test ascertains that some combinations of the two variables are cointegrated which concludes the long-term relationship among the defined variables. The results also indicate for a short run causality from electricity consumption to economic growth and to the CO2 emissions. The results conclude that India should take stringent measures to curb the surging emissions of greenhouse gases in which CO2 has a major portion.
India's primary energy basket is heavily weight in favour of coal, oil and gas (92%) and balance 8% renewables, hydro and nuclear. The eco-friendly energy resources like natural gas and renewables (wind & solar) account only for 9% and 2%. The long term energy demand forecast also suggests contribution of coal, oil and gas to slide down to 87%. The Natural gas demand though on increase but the consumption is constrained due to limited domestic production and inadequacy of LNG import facilities. Considering the huge import bill on oil, gas and coal imports ($150 billion, Kelkar 2013) and the ever increasing concern for environment, the eco-friendly non-conventional resources as shale gas are getting preference. This paper examines the potential contribution from Shale Gas to meet the energy demand to fuel the economic growth of India.
Electricity theft is a growing problem worldwide. India, like many other developing countries, is in the grips of electricity theft. To address this challenge, the country introduced various technological solutions, which failed to realize their promised potential. Despite little success, majority of theft-combat interventions continue to emphasize technology and downplay psycho-social factors. The latter calls for deep exploration as power-utility employees have been found to connive with consumers in majority of electricity thefts. Though, employee theft has been explained by distinct perspectives like sociology, psychology, criminology, organizational science etc., none describes the phenomenon completely. In order to gain a holistic understanding, it is imperative to integrate the said perspectives. That's precisely what this paper attempts- It proposes an integrated conceptual framework of the psycho-social factors that predispose employees to collude with consumers in electricity theft.
Electricity theft is a growing problem worldwide. India, like many other developing countries, is in the grips of electricity theft. To address this challenge, the country introduced various technological solutions, which failed to realize their promised potential. Despite little success, majority of theft-combat interventions continue to emphasize technology and downplay psycho-social factors. The latter calls for deep exploration as power-utility employees have been found to connive with consumers in majority of electricity thefts. Though, employee theft has been explained by distinct perspectives like sociology, psychology, criminology, organizational science etc., none describes the phenomenon completely. In order to gain a holistic understanding, it is imperative to integrate the said perspectives. That's precisely what this paper attempts- It proposes an integrated conceptual framework of the psycho-social factors that predispose employees to collude with consumers in electricity theft.
Social media is the fastest growing area of interest among marketing academicians; however the focus is largely on uses, usage, tools and tactics than understanding where social media might fit in an integrated marketing communication mix with respect to customer engagement. This study aims at highlighting the functional perspectives of social media which contribute towards active customer engagement that benefit the companies in multiple ways. With the help of extensive literature review the study has given justifiable reasons to companies for adopting social media as one of supportive mediums along with traditional media to enrich customer engagement. The findings are of interest to marketers like to explore opportunities unfolded by social media with its functional benefit.
Artificial intelligent methods are being extensively used for oil price forecasting as an alternate approach to conventional techniques. There has been a whole spectrum of artificial intelligent techniques to overcome the difficulties of complexity and irregularity in oil price series. The potential of AI as a design tool for oil price forecasting has been reviewed in this study. The following price forecasting techniques have been covered: (i) artificial neural network, (ii) support vector machine, (iii) wavelet, (iv) genetic algorithm, and (v) hybrid systems. In order to investigate the state of artificial intelligent models for oil price forecasting, thirty five research papers (published during 2001 to 2013) had been reviewed in form of table (for ease of comparison) based on the following parameters: (a) input variables, (b) input variables selection method, (c) data characteristics (d) forecasting accuracy and (e) model architecture. This review reveals procedure of AI methods used in complex oil price related studies. The review further extended above overview into discussions regarding specific shortcomings that are associated with feature selection for designing input vector, and then concluded with future insight on improving the current state-of-the-art technology.
The debate on significance of numerous political, economic and financial indicators driving crude oil prices is perpetual. There is no single indicator which can provide a complete picture of how prices can be determined. Nor a simple combination of input indicators can provide accurate and robust price forecast methods. In particular, feature selection plays a key role in designing a forecasting model for oil prices. However, all existing method of predicting oil prices have accounted for non-linearity, non-stationarity and time-varying structure of crude oil prices but seldom focus on selecting significant features with high predicting power. Besides, there is lack of competent feature selection techniques based on associations and dependency of indicators for designing the input vector of oil price forecast. For this purpose, a novel two-stage feature selection method “MI3Algorithm” is proposed for inferring non-linear dependence between oil prices and strategic indicators driving them by employing interaction information and mutual information as measure of redundancy(or synergy) and relevance. The study targets to figure out the importance and impacting mechanism of key indicators driving crude oil prices based on the proposed feature selection algorithm employing multi-layered perceptron neural network (MLP), general regression neural network (GRNN) and cascaded neural network (CNN) as forecasting engine for oil price prediction. The results confirmed the superiority of proposed algorithm compared to some other methods. Besides its high accuracy, the proposed algorithm provides non-redundant and most relevant features as compared to other methods employed in study.
Geopolitical and economic events had strong impact on crude oil markets for over 40 years. Oil prices steadily rose for several years and in July 2008 stood at a record high of 145perbarrel.Further,itplungedto43 per barrel by end of 2008. There is need to identify appropriate features (factors) explaining the characteristics of oil markets during booming and downturn period. Feature selection can help in identifying the most informative and influential input variables before and after financial crisis. The study used an extended version of MI3 algorithm i.e. I2MI2 algorithm together with general regression neural network as forecasting engine to examine the explanatory power of selected features and their contribution in driving oil prices. The study used features selected from proposed methodology for one-month ahead and twelve-month ahead forecast horizon. The forecast from the proposed methodology outperformed in comparison to EIA's STEO estimates. Results shows that reserves and speculations were main players before the crisis and the overall mechanism was broken due to 2008 global financial crisis. The contribution of emerging economy (China) emerged as important variable in explaining the directions of oil prices. EPPI and CPI remain the building blocks before and after crisis while influence of Non-OECD consumption rises after the crisis.
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With relative changes happening in the area of brand engagement and changing perceptions about brand in the minds of consumers, it has become important for marketers to understand the reactions happening in the market. To understand this change reaction, a new tool called social media has been experienced and experimented by many marketers. Market has made companies witness a lot of activities getting executed everyday which are specific to brand. Circumstances become adverse when social platforms do not entertain brands getting marketed through them. In this review work, we shall get an insight of various challenges faced by marketers while establishing engagements between brands and consumers over social media platforms. Methodology: Secondary literature review on the available papers pertaining to brand engagements and social media has been done. Apart from this, certain articles and journals have been referred to make the work more useful. Findings: Even with the change of time consumers have only shown interests over sales campaigns and hence marketers have no choice left but to entertain existing customers over social media. Acquiring new customer is a far way ahead to be executed via social media. Practical Implications: Marketers have still not used social media, the way and in the manner it can provide opportunities for long term benefits. Their attraction towards social media has only made them look and aim at short term gains.
The purpose of this research is to see various perspectives of Social Media that shall give a meaning to companies to implement it in their marketing strategies. The study also highlights the roles that social media has to play in today’s dynamic landscape of Marketing. Rigorous literature review using existing literature, journals and articles has been done. The findings indicate that there are many logical reasons for marketers to incorporate Social Media in their IMC construct. The findings are of interest to academicians and marketers to understand significant reasons why Social Media is different from other marketing tools and also address the uniqueness of Social Media.
India has tremendous potential for generating clean electricity through Renewable Energy Sources (RES) namely Hydro, Wind and Solar. This potential has been duly recognized and shows India׳s consciousness for reducing carbon footprint as a developing nation. Government of India with an aim to promote clean energy launched Jawaharlal Nehru National Solar Mission (JNNSM) on 11th January 2010, which is one of the eight missions under National Action Plan on Climate Change (NAPCC–2008). This mission visions to install 22,000 MW through grid connected and off grid power plants. Achieving an installed capacity of this quantum is a task full of challenges. To list the possible challenges and suggest a way forward, there is a need to study solar energy sector in India in the past, which has motivated the authors to discuss the evolution of solar energy in India since independence. Through this paper authors have tried to outline the journey of solar energy in India since 1950 till date and highlight the potential issues as barriers and challenges which could impact the ambitious mission taken up by Government of India.
This study will help decision makers and various stakeholders to understand the current status, barriers and challenges for better planning and management in the field of solar energy
Industrial operations could emit harmful pollutants and degrade natural environment, thereby posing a threat to human beings and wildlife (polar bears, panda, penguins, turtles, whales, walrus etc.). Globally manufacturers must ensure that the operations be done as safely and responsibly as possible keeping in line with the three dimensions of triple bottom line. We develop a framework which analyses the various complex relationships involved in a sustainable supply chain with the aid of interpretive structural modeling. The key factors influencing sustainable supply chain were identified based on a thorough literature review and in consultation with rubber industry experts. Further MICMAC analysis was applied to identify the autonomous, linkage, dependent and independent factors.
India is one of the most rapidly developing countries in the world. It is witnessing growing industrialization and thus development. Such rapid development needs energy to progress, which further makes India an energy hungry nation. Currently India depends mainly upon fossil fuels and thus has to pay a huge bill at the end of every contractual period. These bills can be shortened and the expenditures brought down by using and exploiting non-conventional sources of energy. India holds a huge potential for such non-conventional sources of energy. The rapid development of India is not just pressing hard upon its resources but forcing expenditures on the same. There are also some neglected side effects of this development process like, generation of waste. A population of 1.2 billion is generating 0.5 kg per person every day. This, sums up to a huge pile of waste, which is mostly landfilled in the most unhygienic manner possible. Such unmanaged waste not only eats up resources but demands expenditure as well. This can lead to the downfall of an economy and degradation of the nation.Thus, the paper presents waste to energy as a solution to both the problems stated above, using which not only can we reduce the amount of waste, but also produce energy from the same, thus achieving our goal of waste management as well as energy security. The paper presents the current status, major achievements and future aspects of waste to energy in India which will help decision makers, planners and bodies involved in the management of municipal solid waste understand the current status challenges and barriers of MSWM in India for further better planning and management.
India is poised to spend over USD 5.8 billion as part of the National Smart Grid Mission aimed to alleviate India's ailing power sector as part of its 12th Five year plan (2012–2017). The federal government sponsored Restructured Accelerated Power Development and Reforms Program (R-APDRP) is also focused on building ICT capability in the state electricity boards. Presently however, there is no power sector specific cyber security mandates or policies in India. The Stuxnet, Shamoon and Anonymous incidents have shown that cyber-attacks can cause significant damage and pose a risk to National Critical Infrastructure. A lack of security planning as part of designing the Smart grids can potentially leave gaping holes in the country's power sector stability. The paper highlights key cyber security threats across the entire power sector value chain—from generation, to transmission and distribution. It is aimed at building the case for power sector specific cyber security regulations based on the experience of regulators in other critical infrastructure sectors like Banking and Telecom in India and power sector regulations internationally
In this study valuation of operational phase investment related risks in small hydro power project in Uttarakhand state of India is considered. The foremost emphasis of this work is to examine the importance of studying various risk factors related to investment in operational small hydro power project-which is not a common investment practice performed in this particular area. Because of the stochastic nature of variables that compute NPV (net present value)/IRR (internal rate of return), BCR (Benefit cost ratio) it has some uncertainty which cause risk in investment decision. Such external variables are identified based on literature reviews, expert interviews and field survey as follows: capital cost, operational and maintenance, energy generation, environmental hazards, policy changes, social acceptance, etc. The relative importance of these factors are evaluated stochastically and ranked them accordingly. The greatest advantage of this method is that it has simplicity. When dealing with the risk analysis problems, the prevalence of method has been showed: easier and more useful.
This paper outline the business viability of Distributed or Stand-alone hybrid power system consisting of Biomass and Diesel versus Traditional Top down grid connected solar power generation. The environment considered in this paper is for RE. It emphasizes and recommends the use of localized renewable hybrid power generation system in order to ascertain a reliable and self-sufficient system. The localized renewable system also positively influences the macro economic conditions of area by way of optimization of the components size and the capital investment. The main power source of the energy system is considered as biomass generator and suitable supported by Diesel Generators. The NREL HOMER package is used for optimization realization. The Business viability of Stand-alone hybrid power system consisting of Biomass and Diesel versus Traditional Top down grid connected solar power is done on the basis of Net per unit revenue collected post factoring Transmission, distribution, billing and collection inefficiencies.
In many developing countries, the electricity system is too weak to meet growing demand. The availability and reliability of generating capacity is also in short supply. Political interference, subsidized pricing, and corruption weaken the ability of developing countries like India electricity supply system, to finance and deliver service or attract new private investment. Electricity theft can be in various forms of frauds like meter tampering, stealing with illegal connections, billing irregularities, and unpaid bills. This work deals with power economics, policy, regulations and reforms. Random sampling with personal interviews was to be done for primary data collection from domestic users, industrial users, media and power distribution agencies. One more survey for Technology Feasibility of power system has to be done with personal interviews from generation, transmission and distribution units of Electricity system in Kanpur city. A comparative analysis to compare investment in DG versus a large-scale generator in the presence of uncertain demand growth has to be done. Net Present Cost, Cost of Energy, Break even Grid Distance are the three most important output variables of the analysis. The survey data shows that a huge amount of improvement needs in Energy system. This electricity system can be improved by applying technical solutions such as tamper-proof meters, various managerial methods such as inspection and monitoring of distribution system, and in some cases restructuring power systems ownership and regulation.
There has been a surge in the spending in the Power sector in India with an estimated spend of USD 5.8 billion as part of the National Smart Grid Mission with the key objective of turning around India’s ailing Power sector. The focus is also on driving ICT capability with the federal government specially setting up the R-APDRP (Restructured Accelerated Power Development and Reforms Program) to bring about rapid development and modernization of the State Electricity Boards in India. But the most pressing issue right now is the huge threats that cyber attacks pose for the Power sector; and there are currently no specific cyber security mandates or policies in India to thwart the eminent danger looming ahead. Designing Smart Grids without a proper security plan in place can lead to a crisis situation and result in weakening the country’s Power sector stability. The paper highlights key cyber security threats across the entire Power sector value chain. It is aimed at building the case for the Power sector specific cyber security regulations based on the experience of regulators in other critical infrastructure sectors like Banking and Telecom in India and Power sector regulations globally.
Over the years the general insurance companies have been undertaking extensive risk management activities to safe guard the investor as well as investment. In the present day scenario the two aspects which are of great importance to the general insurance industry are firstly the opportunities in the Indian general insurance market and the resulting focus of players on achieving business growth and secondly the ongoing process of calibrated de-tariffing. Though de-tariffing has provided players with significant opportunities in tapping markets and in coming times may result into providing even more opportunities, it has placed the onus of correct pricing on the players themselves. This has resulted in players preparing and emphasizing more on identifying risk parameters and pricing products based on risks. The players under the immediate response to the pressure of a free market scenario, has dropped the rates even in hitherto non-profitable businesses. An efficient risk assessment and management in general insurance industry lays great emphasis due to entry of private players, corresponding policy changes and the present day fact of unprofitable books, erosion of capital resulting from unmanageable claim ratios.
A fact that the grievance redressal complaints of general insurance claims are three times as that of life insurance claims endorses the requirement of a retrospection of claims behaviour of the general insurers in order to minimize the operating losses and ensure operational excellence. Approach: Study of variance and factor analysis has been undertaken for achieving the objective of identifying the factors which govern the claims in general insurance business. In order to understand the dependency of claims over the sectors and segments, statistical hypothesis testing along with cross tab analysis has been conducted. The study also evaluates the relationship of these factors over the sectors and segments by running a multiple regression. Findings: An empirical result of the study proves that there exists an association between the type of sectors i.e. public & private and segments of insurance namely fire, marine and miscellaneous. The study also suggests a claim projection model for the general insurance players. Research limitations: Exclusion of specialized players due to the reason being new entrants and in order to maintain the common parlance of sectors may be a limitation to the study. Value: The study recommends that the insurance players should not treat the claims settlement strategies in isolation of segments. The claims projection model as suggested in the study may prove to be extremely helpful in projecting the claims and in turn reduce the increasing underwriting losses.
Microalgae are receiving increasing attention worldwide as an alternative and renewable source for energy production. Through various conversion processes, microalgae can be used to produce many different kinds of biofuels, which include biodiesel, bio-syngas, bio-oil, bio-ethanol, and bio-hydrogen. However, large scale production of microalgal biofuels, via many available conversion techniques, faces a number of technical challenges which have made the current growth and development of the algal biofuel industry economically unviable. Therefore, in addition to algae culture and growth, it is also essential to develop cost-effective technologies for efficient biomass harvesting, lipid extraction and biofuels production. This review aims to collate and present an overview of current harvesting, oil extraction and biofuels production technologies from microalgae. Since much of the current studies on oil extraction are focused on biodiesel production from microalga, this study, apart from discussing the various biodiesel production techniques in the later sections, has also done a detailed discussion on the production techniques of other biofuels.
In the present article we discuss the generalized class of synthetic estimators for estimating the population mean of small domains under the information of two auxiliary variables, and describe the special cases under the different values of the constant beta involved in the proposed generalized class of synthetic estimator. In addition we have taken a numerical illustration for the two auxiliary variables and compared the result for the synthetic ratio estimator under single and two auxiliary variables.
One of the key challenges in integrated wireless and mobile networks is to efficiently support multi-class services as each type of services has distinct characteristics and quality of service (QoS) requirements. Problems in handoff algorithm or its parameters may lead into call drops with a direct effect on user satisfaction. This is particularly critical for 3G systems, where high data rate users will be prime candidates for being dropped. Unnecessary handoff leads to degraded call quality and waste of capacity in signaling. Since the cell-size is constantly decreasing, therefore it is important to devise a handoff algorithm which identify users with different mobility and data rate characteristics and maximize the utilization of network infrastructure. A Multiple Queuing System for handoff in integrated real-time and non-real time service with priority reservation and preemptive priority handoff scheme is being analyzed which categorizes the service calls into four different types, namely, real time and non-real time service originating calls, and real-time and non-real-time handoff request calls and divide the channels among these four types of services according to their priorities. The system is modeled using a multidimensional Markov chain and a numerical analysis is presented to estimate blocking probabilities of originating calls, forced termination probability, and average transmission delay. Our results show that the predictions of the analytical model are in very good agreement with simulation results. Scheme significantly reduces the forced termination probability of real-time service calls. The probability of packet loss of non real-time transmission is shown to be negligibly small, as a non-real-time service handoff request in waiting can be transferred from the queue of the current base station to another one.
In the current scenario of depleting energy resources, increasing food insecurity and global warming, Jatropha has emerged as a promising energy crop for India. The aim of this study is to examine the life cycle energy balance for Jatropha biodiesel production and greenhouse gas emissions from post-energy use and end combustion of biodiesel, over a period of 5 years. It’s a case specific study for a small scale, high input Jatropha biodiesel system. Most of the existing studies have considered low input Jatropha biodiesel system and have used NEB (Net energy balance i.e. difference of energy output and energy input) and NER (Net energy ratio i.e. ratio of energy output to energy input) as indicators for estimating the viability of the systems. Although, many of them have shown these indicators to be positive, yet the values are very less. The results of this study, when compared with two previous studies of Jatropha, show that the values for these indicators can be increased to a much greater extent, if we use a high input Jatropha biodiesel system. Further, when compared to a study done on palm oil and Coconut oil, it was found even if the NEB and NER of biodiesel from Jatropha were lesser in comparison to those of Palm oil and Coconut oil, yet, when energy content of the co-products were also considered, Jatropha had the highest value for both the indicators in comparison to the rest two.
There are several indicators and determinants of health status in the systems that affected the behavior of the population regarding their good health as well as the development. In this article we make use of three health indicators namely crude birth rate, crude death rate and infant mortality rate and four determinants namely per capita income, number of government hospitals, government expenditure on health as a percentage of total government expenditure. We demonstrate the major trends in the determinants and the indicators of health status in India during the time period of three consecutive censuses from year, 1981-2001. Further using multiple regressions and model fitting we also estimate the effect of determinants of health on the indicators of health status in the society which are the main responsible aspect of development of a nation.
Futures market performs an important function which is to provide effective hedging besides price discovery at distant future date to the market participants. The hedging effectiveness of the futures contract shows its utility in reducing the amount of risk. We estimated the effective hedge ratio and its hedging effectiveness for the S&P CNX Nifty futures using daily data from 12 June 2000 to 24 December 2008 by three models. The study found that Nifty futures contract provides effective hedging to the market players for hedging purpose.
This paper defines and discusses a generalized class of composite estimators for small domains, using auxiliary information, under systematic sampling scheme. The generalized class of composite estimators, among others, includes a number of direct, synthetic and composite estimators. Further, it demonstrates the use of the estimators belonging to the generalized class for estimating crop acreage for small domains and also compares their relative performance with the corresponding direct and synthetic estimators, through a simulation study.
This paper defines and discusses a generalized class of synthetic estimators for small domain, using auxiliary information, under systematic sampling scheme. The generalized class of synthetic estimators, among others, includes the simple, ratio and product synthetic estimators. Further, it demonstrates the use of the generalized synthetic and ratio synthetic estimators for estimating crop acreage for small domain and also compares their relative performance with direct estimators, empirically, through a simulation study.
This paper studies performance of synthetic ratio estimator and composite estimator, which is a weighted sum of direct and synthetic ratio estimators, under Lahiri – Midzuno (L-M) sampling scheme. Both the estimators under L-M scheme are unbiased and consistent if the assumption of synthetic estimator is satisfied. Further, this paper compares performance of the estimators empirically under L-M and SRSWOR schemes for estimating crop acreage for small domains. The study suggests that both the estimators under L-M scheme perform better than, under SRSWOR scheme, as having smaller absolute relative biases and relative standard errors.
The purpose of this chapter is to identify the dimensions of green supply chain and their impact on manufacturing practices. In this study, the authors used two extended strategies. First thorough review of literature was done considering articles from reputed journals. Second the factors identified from literature review was further refined through experts by forming a problem solving group consisting of seven experts from the manufacturing sector. These factors were used to develop the green supply chain management model using Interpretive structural modeling. Further MICMAC analysis was used to identify the driving and dependence power of the factors. The results of the analysis are very encouraging. Finally, the authors have presented the relationship management strategy for sustainable manufacturing practices.
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I am currently working as Professor & Director “Office of Doctoral Studies” at O.P. Jindal Global University, Sonipat. As Director of “Office of Doctoral Studies”, I have many administrative responsibilities related to academic planning and developing a strong research base to promote research and research culture at Jindal Global University. As a Professor, I am teaching my students across all the schools at JGU. Teaching has been always being my passion, as it reveals my inner desire to help others, to impart my knowledge to them, and to sail in other people's minds the minds of others. I am very self-motivated at teaching and give my best to improve student understanding.
I started teaching in the year 2002 at J.N.V. University, Jodhpur. At J.N.V. University, I taught courses like sample survey, applied statistics, and statistics for physical education. Then at Banasthali University till 2008, I taught Advance Sample Survey, Demography, Applied Statistics, Statistical Inference, Multivariate Statistics, etc. After 2008, I joined at University of Petroleum & Energy Studies (UPES), Dehradun, and taught various courses like Applied statistics, Research Methodology, Quantitative techniques,Data Mining, to the management students. After joining Jindal Global University in 2016, I develop a course on predictive data mining & data visualization and taught the same through Tableau, Excel & R software. Through the Quantitative Research Methods course, I am trying to develop the basic research understanding of my Ph.D. students at JGU.
I believe that to help students develop questioning and problem-solving skills, a teacher should first create an interactive environment, maintaining a natural chain of thought that evolves from simple to complex reasoning. In nutshell,I think that teaching is a process that helps both the students and the teacher.
Curent Teaching |
Teaching History |
Predictive Data Mining with Excel & R
Data Visualization with Tableau Quantitative Research Methods Data Science Methodolog Predictive Modelling Marketing Research |
Sample survey
Applied statistics with SPSS Statistics for physical education Advance Sample Survey & Demography Statistical Inference Multivariate Statistics Research Methodology Quantitative techniques Data Mining |
S.No. | Name of Scholar | Thesis Title | Status |
1 | Namita Pragya, Head – Center for Excellence in Energy, Adani Institute of Infrastructure Management |
Production of Green diesel from Jatropha & Algae | Degree Awarded |
2 | Neha Sehgal, (Senior Lecturer of Data Science at Sheffield Hallam University. U.K.) |
The Drivers Of Oil Prices: A Data Mining Approach | Degree Awarded |
3 | Karan Kapoor, Brunswick East, Victoria, Australia |
Barriers & Challenges faced by the Solar PV (grid-connected) Power plant in India | Degree Awarded |
4 | Neha Chhabra Roy, SVKM's Narsee Monjee Institute of Management Studies (NMIMS), Bangalore |
Risk identification and Assessment for investment decision making in small Hydropower projects of Uttarakhand | Degree Awarded |
5 | Tanushree Sharma, (Professor & Associate registrar, O.P Jindal Global University) |
Workplace factors predisposing employees to connive with customers in electricity theft in the Indian power distribution sector. | Degree Awarded |
6 | Anand V. Kumar, (Director, Managed Security Services at IBM Greater Atlanta Area) Atlanta |
Cybersecurity threats in the power sector: Need for a domain-specific regulatory framework in India | Degree Awarded |
7 | M. Tomar, (Associate professor, O.P. Jindal Global University, Sonipat.) |
Use of Social Media as a tool for Marketing Communication by Automotive Lubricant Companies in India | Degree Awarded |
8 | Vikas Manoria, Cloud Solution Architect(IBM) |
Complexities & challenges in online assessment in higher education | Working on Thesis |
9 | Akash Saharan, Doctoral Research Fellow at JGBS, JGU |
The impact of Entrepreneurial Orientation, Market Orientation, and Human Capital on SME performance: The mediating role of Innovation and Degree of Internationalization | Thesis Submitted |
10 | Swaroopa Karnick, IAS , Chief Executive Officer, Dharwad Zilla Panchayat, Karnataka |
Integrated approach of policy instruments for the digital transformation of MSMEs in Entrepreneurial ecosystems | Working on Thesis |
11 | Kavita R. Garg | Modeling And Analysis Of Factors Affecting Digital Therapeutics Adoption In Diabetes Management | Working on Thesis |
12 | Ayush Gupta, (CGM, HR) GAIL (India) Limited. |
Strategic Drivers for Growth of Natural Gas Sector in India by 2030 | Working on Thesis |
GUIDED AS CO- SUPERVISOR |
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1 | B.S. Negi, Former PNGRB Member |
Factors Influencing Shale Gas Exploration & Exploitation In India | Degree Awarded |
2 | Surajit Bag, Associate Professor University of Johannesburg, South Africa. |
Developing A Green Supply Chain Management Model For The Indian Rubber Goods Manufacturing Sector | Degree Awarded |
3 | Lov Kumar Mishra, Regional CTO, Nigeria, Globacom |
The Bottom-Up Distributed Generation for Uttar Pradesh, India | Degree Awarded |
4 | Ganesh Vishwakarma, Director of project & Business planning, Steel Authority of India. |
Identifying project risk factors affecting project cost performance in the steel industry: An Indian perspective | Degree Awarded |
5 | Sachin Kumar (Assistant Professor, Manipal University Jaipur) |
Mindfulness and Sustainable Consumption Behaviour: A Salutary Nexus | Degree Awarded |
6 | Nisha Phakey (Assistant Professor, Christ University Delhi) |
Development and validation of brief Social Cognition Scale for Young Adults and Adolescents | Degree Awarded |
7 | Monica Shani, Doctoral Research Fellow at JGLS, JGU |
Cyber Security Awareness for Indian school learners: Conceptual framework & implementation strategies | Degree Awarded |
8 | Shankey Verma, Doctoral Research Fellow, Jindal Institute of Behavioural Sciences (JIBS), JGU |
Prevalence of Intimate Partner Violence (IPV) and Impact on Psychological Outcomes and Academic Performance among Indian Female Students in Higher Education Institutions (HEIs) | Degree Awarded |
9 | Megha Yadav, Doctoral Research Fellow, Jindal Institute of Behavioural Sciences (JIBS), JGU |
Safety Behaviour among Interstate Migrant Blue-collar Construction Workers in National Capital Region (India): An investigation into the role of psychological capital and collective resilience as antecedents, physical and psychosocial safety climate as mediators, and gender as a moderator | Working on Thesis |
10 | Shalika Rakesh Doctoral Research Fellow at JGBS, JGU |
An Investigation Into Co-Occurrence Of Engagement And Burnout Among Faculty Members Of Indian Higher Education Institutions | Working on Thesis |
11 | Anupama Raj | Poetic metaphors in written leadership communication: A qualitative experiment of employees’ sense making and action | Working on Thesis |
I would be happy to talk to you if you need my assistance in your research/project work. I am also open to provide my extended support and services related to your needfor business administration. You may contact me through email or mobile for getting consultancy support for your company.
You can find me at my Residence located in Tulip Grand, Near O.P.Jindal Global University, Sonipat, Haryana.
I am at my Residence every day from 7:00 until 10:00 am and After 6:00 pm to 9:00 pm, but you may consider a call to fix an appointment.
You can find me at my office located at Office of Doctoral Studies, A-374, T3 block, 4th floor, O.P. Jindal Global University, Sonipat, Haryana.
I am at my office every day from 10:00 until 06:00 pm, but you may consider a call to fix an appointment.