Dr. Harjit Singh
@scmsnoida.ac.in
Professor
Symbiosis International University Noida
Dr. Harjit Singh, a regular contributor to National and International journals, is Professor (Finance) at Symbiosis International University Noida, India. He has over two decades of rich experience in Teaching, Research, and Consultancy. He has extensively travelled in and outside India to conduct workshops, Seminars, and FDPs. He has written several textbooks, study material books, edited books, and case studies with International Reputed publication houses. His area of research is Financial Management, Business Restructuring, Blockchain, and Corporate Governance.
EDUCATION
MFC (Gold Medalist), M.Phil, PhD
Scopus Publications
Scholar Citations
Scholar h-index
Scholar i10-index
Scopus Publications
Vedangi Gupta, Avneet Singh, Harjit Singh, and Eeshaan Chaudhary
IGI Global
This study mainly explores the next phase of generative artificial intelligence and its benefits in healthcare. This work explores the changes artificial intelligence can bring to this sector, including artificial neural networks and adaptive autoencoders to develop self-healing models by collecting patient information, data, and existing research studies. These artificial intelligence systems can create curated plans for treatment that will benefit the patient. This will help improve treatment outcomes while reducing their side effects and overall outcomes for everyone with the disease. This chapter also explores the commitment of artificial intelligence in healthcare, discusses the issues and ethics, and suggests fields for future research, studies, and applications.
Sonam Rani, Ajit Mittal, and Harjit Singh
IEEE
This research aims to investigate the user experience of customers interacting with robo-advisors and assess their satisfaction levels. The study will identify key usability factors, interface design elements, and personalized features that influence customer satisfaction and loyalty in robo-advisor platforms. By conducting a multi-dimensional analysis, incorporating qualitative and quantitative research methods, this research seeks to provide actionable insights for improving the user experience and enhancing customer satisfaction in robo-advisor services. Robo-advisor is the initiative taken by the many banks to enhance the customer experience also reduce the cost of services. This can be done by using chat bots and there are many other AI enabled services that is provided by banks like face recognition, voice assistance, biometrics etc. Voice-assistance and chat bots are the mostly used robo-advisor services by customers of banks for mitigation of risk. This study conduct to explore the relationship between user experience, satisfaction levels and long term loyalty to robo-advisor platforms. This study used primary and secondary data and secondary data collected from research papers, journals and articles. The investigation synthesises and evaluates pertinent articles and research papers released between 2011 and 2023 using a comparative exploration pattern.
Neha Puri and Harjit Singh
Apple Academic Press
Nisha Nisha, Neha Puri, Namita Rajput, and Harjit Singh
Emerald
Purpose The purpose of this study is to analyse and compile the literature on various option pricing models (OPM) or methodologies. The report highlights the gaps in the existing literature review and builds recommendations for potential scholars interested in the subject area. Design/methodology/approach In this study, the researchers used a systematic literature review procedure to collect data from Scopus. Bibliometric and structured network analyses were used to examine the bibliometric properties of 864 research documents. Findings As per the findings of the study, publication in the field has been increasing at a rate of 6% on average. This study also includes a list of the most influential and productive researchers, frequently used keywords and primary publications in this subject area. In particular, Thematic map and Sankey’s diagram for conceptual structure and for intellectual structure co-citation analysis and bibliographic coupling were used. Research limitations/implications Based on the conclusion presented in this paper, there are several potential implications for research, practice and society. Practical implications This study provides useful insights for future research in the area of OPM in financial derivatives. Researchers can focus on impactful authors, significant work and productive countries and identify potential collaborators. The study also highlights the commonly used OPMs and emerging themes like machine learning and deep neural network models, which can inform practitioners about new developments in the field and guide the development of new models to address existing limitations. Social implications The accurate pricing of financial derivatives has significant implications for society, as it can impact the stability of financial markets and the wider economy. The findings of this study, which identify the most commonly used OPMs and emerging themes, can help improve the accuracy of pricing and risk management in the financial derivatives sector, which can ultimately benefit society as a whole. Originality/value It is possibly the initial effort to consolidate the literature on calibration on option price by evaluating and analysing alternative OPM applied by researchers to guide future research in the right direction.
Harjit Singh and Neha Puri
Springer Nature Singapore
Archana Malik and Harjit Singh
Inderscience Publishers
Harjit Singh and Avneet Singh
Informa UK Limited
Harjit Singh, Geetika Jain, Nishant Kumar, and Loha Hashimy
IGI Global
The concept of fashion has been coupled with technology, where technology has become the protagonist. The transparency between an organization and a customer works as a catalyst, and the customer has taken a more mainstream role. With blockchain technology, companies can reconnect with customers and customers can track the journey of a product from its raw materials to the finished goods. The primary focus of the study is on services and data collected from the following sectors, namely fashion, apparel, and online platforms. The author's main goals are (1) to illustrate an overview of how big data is transforming the service industry, especially the fashion and design sector, and (2) to present various mechanisms adopted in the service industry. The study aims to investigate a model that fits through EXT-TAM and uses additional attributes of blockchain technology with a special reference to fashion apparel. The findings of this study depict a model, where PEOU, PU, and attitude are the major constructs and present a win-win scenario for both the customer and the organization.
Neha Puri, Harjit Singh, Sujajta Khandai, and Misbah Ul Islam
IEEE
With the advancements in the information and communication technology (ICT) and acceptance to Industry 4.0 standards, it has become indispensable for the companies, especially export firms to replace their domestic accounting standards with "International Financial Reporting Standards" (IFRS), India is not an exception. With the conversion of rules- based on a principal-based set of accounting standards, it has become essential for both the education planners and educators to incorporate IFRS in the curriculum with respect to industry 4.0. The data has been analyzed with respect to the requirements of the adoption of IFRS. The data has been collected from the respondents pursuing chartered accountants and budding professionals in the field of accounting & finance through the questionnaire. This study is an attempt to examine the impact of extent of introducing IFRS in the accounting curriculum and its learning outcome.
Abdul Wajid and Harjit Singh
Inderscience Publishers
Seema Tewari, Harjit Singh, Shobhit Wadhwa, and Deepak Tandon
University of Wollongong Library
Impact Investing is a community of investors willing to create social and environmental impact along with financial returns by investing either directly with Base of Pyramid[1] (BoP) enterprises or indirectly through enterprises that help in creating impact by investing in BoP organizations. Adoption of SDGs[2] quantified the expectation paradigm of the global community for social, environmental and economic achievable and projected/targeted achievement of SDGs by 2030 made the governments, businesses, institutions daunted with the task in hand hence, it is imperative for investing community to contribute its share as well. With high social need and underserved population India has become a test bed for impact investing. However, with increasing impact investing, Impact Measurement and Management (IMM) gains significant importance as it allows investors to evaluate impact and channelize fund to most effective solutions. The present study conducted for year 2019 not only attempts to explore impact investing landscape in India and its future dimension but it simultaneously does content analysis of impact report of investors using impact value chain[3] and indicators developed on the basis of SDGs targets and indicators. The analysis aims to establish a link between developed indicators and impact, the link once established, developed indicators will provide agile, cost effective, quantifiable and measurable basis to impact that has worldwide acceptance. [1]Base of Pyramid refers to the poorest two-third of the economic human pyramid living in abject poverty. [2]SDGs, adopted in 2015 by all UN member states, are universally accepted goals and targets under goals to guide sustainable development and create a sustainable world for all. [3]Impact Value chain is a tool build on theory of change to illustrate how enterprise activities lead to desired outcome and impact by setting a relationship between activities, output, outcome and impact.
Neha Puri, Harjit Singh, and Vikas Garg
Springer Singapore
Neha Puri and Harjit Singh
Springer Science and Business Media LLC
Neha Puri and Harjit Singh
Springer Science and Business Media LLC
Geetika Jain, Harjit Singh, K. R. Chaturvedi, and Sapna Rakesh
Emerald
PurposeThe study is an attempt to explore much talked but less understood issue of “blockchain in logistics industry” in modern perspective. The customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model” by using attitude, perceived usefulness (PU), perceived ease of use (PEOU), behavioral intention and use behavior.Design/methodology/approachData has been collected through online and offline medium, where active 240 responses have been collected finally using convenience sampling. Confirmatory factor analysis with structural equation modeling (SEM) was carried out for data analysis.FindingsThe customers' acceptance of blockchain technology in logistics and supply chain is tested through “Technology Acceptance Model.” The findings reveal model fit where PEOU, PU and attitude are the major constructs of the model to realize the substantial gains in logistics process efficiency.Research limitations/implicationsConvenience sampling has been considered for the study to collect the data of online users of various technology applications for tracking and shipment detail, whereas a more specified method sampling can be considered for the future research. The study has been conducted in the Indian context, which has been considered as the limitation pertaining to generalization across countries and industries.Practical implicationsThe findings of this study will be helpful for market practitioners to build transparency between customers and industry to overcome the frictions in logistics. Blockchain will help in monitoring the performance history and previous commitments of logistics professionals resulting in selecting a responsible logistics solution provider. Access to critical data by the authorized member of the supply chain will reduce unsubstantiated disputes.Social implicationsBlockchain technology will be available to everyone on the network. This will bring transparency and help logistics professionals such as carriers, shippers and brokers to detect early frauds and prevent thefts. It will increase customer trust toward any financial transaction for tracking the ownership of titles.Originality/valueBlockchain technology is envisioned to be a technology that could be a game-changer for decentralizing infrastructure, introducing transparency and building trust in the supply chain. The current study is a novel addition to the literature where blockchain technology enables the indisputable storage of verified data that was previously kept in safeguarded silos.
Harjit Singh, Purva Grover, Arpan Kumar Kar, and P. Vigneswara Ilavarasan
Emerald
Purpose The purpose of this paper is to summarize the literature of electronic government frameworks and models to identify various constructs and their relationship to measure the performance of e-government projects. Design/methodology/approach In total, 77 publications were identified from Scopus database after using exclusion and inclusion criteria. A total of 136 constructs were mapped across five categories. Further using network science, communities of usage of these constructs across different studies were identified. Findings Dominant constructs used across studies were ease of use, usefulness, user satisfaction, infrastructure, website maturity, security, user trust, transparency, empowerment, operational efficiency, service quality and information quality. This review offers directions for future research in terms of potential for constructs, which have been explored lesser in the existing literature. Research limitations/implications The study provides direction for the usage of theoretical lenses, constructs and association among usage for the evaluation of e-government projects, which have been used less in existing literature, and thus, has higher needs for greater exploration. Search scope is limited to Scopus database, which is one of the largest citation database. Practical implications It gives information to the policymakers about the importance of the dominant constructs such as user satisfaction, usefulness, ease of use, efficiency and quality, which have been used across the spectrum of studies of e-government performance assessment frameworks and models. Practitioners need to accommodate the relevance of these factors while designing processes and key performance indicators. Originality/value This study analyzes the e-government assessment frameworks and gives direction to theory building for future studies.
Harjit Singh, Geetika Jain, Alka Munjal, and Sapna Rakesh
Emerald
Purpose The purpose of this paper is to determine the stakeholders’ acceptance on blockchain and to investigate the model fit by using “Technology Acceptance Model” with special reference to corporate governance through cryptography to resolve the decades-old problems of financial record-keeping. Design/methodology/approach The whole analysis has been performed in the two steps, i.e. confirmatory factors analysis and structural equation modeling, to prove model fit between behavioral intention and actual behavior for using blockchain technology. Total 223 respondents have been selected, and the selection of the respondent is primarily on the basis of their previous experience with trading corporate equities. Findings The study determines empirically all the mentioned relationships of attitude, perceived ease of use and perceived usefulness with the behavioral intention as per the conceptual model to prove the relationship. The results of the manuscript shows the model fit indexes for various constructs are prove the model fit as per the theorized model. The values of the various indexes are found to be under the permissible range which explains the relationship of various constructs based on the theorized model. Research limitations/implications Despite, the limitations in terms of selection of sampling methods, outcome and the interpretation, the results proves the fit with the theoretical framework. The major implication is to understand the real-time use of blockchain technology for the transfer of shares from one party to other. Practical implications Stakeholders in corporate governance namely customers, creditors, suppliers, community, employees, owners, investors, trade unions and social activists could benefit in different ways. Investors could benefit from being able to purchase equity at low price and to sell them into a market with greater liquidity, but they would found it difficult to camouflage their trades. Social implications The study opines that virtually all aspects of the corporate governance can be improved through the adoption of this technology resulting in greater transparency, improved liquidity and lowering costs. Originality/value This study will be a reference for global players in the financial industry that have started investing in this innovative technology vis-à-vis recent announcement of adoption of blockchain by global exchanges including NASDAQ, NYSE and Deutsche Borse, as a new method for trading, tracking ownership and monitoring systemic risk for strengthening corporate governance mechanism. This study will have a significant index for future reference where the technology adoption will be tested to have better corporate governance which will be useful for academics and professionals.
Abdul Wajid, Harjit Singh, and Abdul Aziz Ansari
Associated Management Consultants, PVT., Ltd.
Dikshita Anon and Harjit Singh
Associated Management Consultants, PVT., Ltd.
Volatility has been used as an indirect means for predicting risk accompanied with an asset. Volatility explains the variations in returns. Forecasting volatility has been a stimulating problem in the financial systems. This study examined the different volatility estimators and determined the most efficient volatility estimator. The study described the accuracy of the forecasting technique with respect to various volatility estimators. The methodology of volatility estimation included Close, Garman-Klass, Parkinson, Roger-Satchell, and Yang-Zhang methods and forecasting was done through the ARIMA technique. The study evaluated the efficiency and bias of various volatility estimators. The comparative analyses based on various error measuring parameters like ME, RMSE, MAE, MPE, MAPE, MASE, and ACF1 gave the accuracy of forecasting with the best volatility estimator. Out of five volatility estimators analyzed over a period of 10 years and after critically examining them for forecasting volatility, the research obtained Parkinson estimator as the most efficient volatility estimator. Based on various error measuring parameters, Parkinson estimator was found to be the most accurate estimator based on RMSE, MPE, and MASE in forecasting through the ARIMA technique. The study suggested that the forecasted values were accurate based on the values of MAE and RMSE. This research was conducted in order to meet the demand of knowing the most efficient volatility estimator for forecasting volatility with high accuracy by traders, option practitioners, and various players of the stock market.
Rajiv Kumar Garg, Anish Sachdeva, and Harjit Singh
Springer Singapore
Nikunj Aggarwal and Harjit Singh
University of Wollongong Library
Around the globe, women’s income and wealth are increasing as never before. Prevailing economic, demographic, and technological changes are growing women’s financial strength and independence. Be it finance, marketing, supply chain or ICT based industry, women have made incredible strides, both at professional and social fronts, particularly in the two decades. Today they are better educated, well placed and have greater accountability in the corporate world and are frontrunners in many professions. Consequently, women, particularly in developing countries like India and China have become economic powerhouses. They not only significantly contribute to GDP but also are becoming a substantial untapped market for the wealth management industry. In this context, this study is an attempt to discuss the much talked about, but less understood, issue of women’s wealth management in the Indian context. The study is intended to explore financial planning awareness among working women and their attitude towards wealth management. The findings will help wealth managers and financial planners to develop a deeper understanding of female investors’ goals and priorities, investment patterns of the working women and to gain insight into gender specific investment behaviour of Indian investors.
Harjit Singh, Rajiv Kumar Garg, and Anish Sachdeva
Emerald
PurposeThe purpose of this paper is to help supply chain (SC) decision makers successfully penetrate through SC collaboration and strengthen their SC in the global market by understanding collaborative activities, and understand how these activities are related to each other in the SC.Design/methodology/approachThis paper develops a set of collaborative activities from literature, and the developed model is helpful for SC decision makers to monitor their SC activities and take corrective actions to improve collaboration in their SC by using interpretive structural modeling (ISM) and MICMAC analysis.FindingsThis study reveals that collaborative activities increase the value of whole SC. The various activities are modeled on the basis of “an activity influencing other activities” and “an activity influenced by other activities,” which is useful for SC managers to take a decision.Research limitations/implicationsThe current study is literature based; therefore, there would be need of more explanation of the activities which lead to understand and implement SC collaboration in case of service and manufacturing industry.Practical implicationsThe model of this study is helpful for decision makers to implement supply chain collaboration (SCC) and to understand various SCC activities on the basis of their driving and dependence power.Originality/valueThis research provided insight into skills needed for SC decision makers to implement collaboration in the SC using ISM. The results of the study could be adopted to monitor the existing SCC program or design new collaboration program to meet the global market requirements. To the best of knowledge, there is no reference that discusses SC collaborative activities on the basis of their driving and dependence powers.
Abdul Wajid et al., Abdul Wajid et al., and
Transstellar Journal Publications and Research Consultancy Private Limited
Urvashi Varma, Harjit Singh, and Alka Munjal
University of Wollongong Library
The share buyback regulation was enacted by the Government of India (GOI) in 1998 with an objective to revive the fast declining Indian capital markets and protect the interest of the investors and companies from hostile takeover bids [1] . Until 2004, the buyback process did not gain any momentum, but the year 2004 witnessed a series of share buyback announcements and this process has continued until the present day. There is much discussion in media and financial circles about this issue, but little effort was made to know the reasons behind such buyback decisions. The present study has analyzed the corporate actions such as the "free cash" policy, dividend distribution, change in capital structure and lower profitability while deciding interpreting the intent behind these ‘tender offer buyback' and ‘open market buyback' offers between January 2004 to December 2017.The study uses a sample of ninety open market repurchasing companies with a similar number of non-repurchasing companies and of fifty-four tender buyback companies with fifty-four non-repurchasing companies in the same industry having similar market capitalization and listed on Bombay stock exchange (BSE). To investigate the drivers of open market buyback and tender offer buyback in India, a Tobit regression analysis has been used. The study concludes that ‘Tender offer buyback' is used more predominantly for capital structure corrections, while in the case of open market repurchase in India, dividend substitution and capital structure correction act as the key drivers. Whether ‘size of the firms' make any significant difference or not, study revealed positive impact on the motive for buybacks. A hostile takeover is a corporate phenomenon that entails the acquisition of a certain block of equity shares of a company giving the acquirer a larger stake in the company than its promoters. That enables the acquiring company to exercise control over the affairs of the company.