Dr. ALEEM ANSARI

@siu.edu.in

Assistant Professor
Symbiosis International University



              

https://researchid.co/aleem.ansari
6

Scopus Publications

21

Scholar Citations

3

Scholar h-index

1

Scholar i10-index

Scopus Publications

  • Challenges Hindering the Digitalization and Innovation of Smart Real Estate in India: A Managerial Insight into Technology Non-Adoption
    Aleem Ansari, Vikrant Vikram Singh, and Aditya Kumar Gupta

    IEEE
    This research investigates the sluggish adoption of disruptive digital technologies (DDTs) in the global real estate sector, with a specific focus on the Indian market. Analysing barriers to digital transformation, the study applies Pythagorean Fuzzy Sets methodologies to quantify challenges, prioritizing technological, organizational, and environmental obstacles. Key hindrances include high implementation costs, limited market data access, organizational resistance to innovation, and external environmental factors. The study advocates for a shift toward Industry 4.0 standards, emphasizing the need to address technological complexities and internal organizational challenges. Insights from experts in telecommunications, information technology, and smart city development inform proposed strategies to facilitate the integration of digital innovations in the Indian real estate landscape. This research contributes theoretical and practical implications, offering actionable strategies for policymakers, industry leaders, and innovators to navigate complexities and promote the adoption of smart real estate technologies on a global scale.

  • Machine Learning in Fintech
    David Campbell, Aleem Ansari, and Vikrant Vikram Singh

    Productivity Press

  • Future of Fintech
    Harendra Singh, Aleem Ansari, and Vikrant Vikram Singh

    Productivity Press

  • Relation between Fintech Trends and Digital Finance: A Bibliometric Analysis
    Sana Fatima, Vartika Kapooor, and Aleem Ansari

    Productivity Press

  • Assessment of Metaverse-Based Digital Learning Systems in Higher Education
    Vikrant Vikram Singh, Aleem Ansari, and Aditya Kumar Gupta

    IEEE
    In recent years people have felt the importance of technology-driven infrastructure in many areas including higher education. Teachers' researchers and students have felt a very strong need for advanced technology-driven platforms in higher education scenarios. The main focus of this study is on how successful metaverse-driven learning systems are. This study looks at the influencing factors of metaverse technology-based digital learning platforms in higher education institutions. To properly examine the various driving factors of Metaverse-based digital learning platforms used by various higher education institutions, several important aspects of these systems were gleaned from the available literature, and several noteworthy articles were chosen from the literature. Several influencing factors of metaverse-based learning systems are identified and ranked using the analytical hierarchy process (AHP) according to important variables and their auxiliary elements. Pythagorean Fuzzy-Delphi was used to address the option's ambiguity. A threshold value of 0.6 was applied and various capabilities were recognized and accepted based on the $\\mathrm{d}_{\\mathrm{f}}\\ (\\alpha)$ value. The difference matrix, interval multiplicative matrix, determinacy value matrix, and normalized priority weight were created using the Pythagorean Fuzzy-Delphi method. Capability's priority rating was established as Push > Mooring > Pull based on Normalized Weights of 0.271, 0.402 and 0.327 respectively. Further various sub-criteria were ranked based on their global ranks obtained from their Pythagorean fuzzy weights and de-fuzzified values. The study's findings showed why metaverse-based systems in different higher education institutions are successfully used to create digital learning systems.

  • Do investors herd in emerging economies? Evidence from the Indian equity market
    Aleem Ansari and Valeed Ahmad Ansari

    Emerald
    PurposeThe purpose of this study is to empirically examine the presence of herding behavior of Indian investors using daily sample data drawn from the Standard and Poor's (S&P) Bombay Stock Exchange-500 Index over the period 2007–2018.Design/methodology/approachThe study employs the model proposed by Chang et al. (2000), taking stock return dispersion as a measure to capture herding. The empirical results demonstrate the absence of herding behavior in all market states, that is, normal, up and down market conditions for the overall period.FindingsContrastingly, the study found negative herding behavior, which underlines that individuals are taking the decision away from the market consensus. The subperiod analysis corroborates the negative herding behavior. The results remain invariant across large, mid and small-capitalization firms except in one year, that is, 2009 for small firms. While using liquidity and sentiment as variables to examine herding, the study finds some evidence of herding behavior for high market liquidity state and sentiment. The findings of negative herding shed new light on herding behavior in the Indian stock market.Originality/valueThis pattern of behavior may indicate irrationality of investor behavior and the presence of noise traders who mistrust market-wide information. Behavioral factors such as overconfidence may explain this pattern of behavior.

RECENT SCHOLAR PUBLICATIONS

  • Machine Learning in Fintech
    D Campbell, A Ansari, VV Singh
    The Adoption of Fintech, 206-217 2024

  • Future of Fintech
    H Singh, A Ansari, VV Singh
    The Adoption of Fintech, 267-276 2024

  • Relation between Fintech Trends and Digital Finance: A Bibliometric Analysis
    VK Sana Fatima Aleem Ansari
    The Adoption of Fintech 2024

  • Assessment of Metaverse-based digital learning systems in Higher Education
    AKG Vikram Vikrant Singh, Aleem Ansari
    4th International Conference on Computation, Automation and Knowledge 2023

  • Do investors herd in emerging economies? Evidence from the Indian equity market
    A Ansari, VA Ansari
    Managerial Finance 47 (7), 951-974 2021

  • Investor herding behaviour in the Indian equity market: Evidence from quantile regression
    A Ansari
    e-journal-First Pan IIT International Management Conference–2018 2020

  • Does herding exist in lottery stocks? Evidence from the Indian stock market
    A Ansari, T Aziz, VA Ansari
    Evidence From the Indian Stock Market (February 12, 2020). Applied Finance 2020

  • Herding behaviour in Indian equity market: a quantile regression approach
    A Ansari
    American Journal of Finance and Accounting 6 (1), 38-55 2019

  • Herding in the stock market
    A Ansari
    Aligarh

MOST CITED SCHOLAR PUBLICATIONS

  • Do investors herd in emerging economies? Evidence from the Indian equity market
    A Ansari, VA Ansari
    Managerial Finance 47 (7), 951-974 2021
    Citations: 12

  • Does herding exist in lottery stocks? Evidence from the Indian stock market
    A Ansari, T Aziz, VA Ansari
    Evidence From the Indian Stock Market (February 12, 2020). Applied Finance 2020
    Citations: 5

  • Herding behaviour in Indian equity market: a quantile regression approach
    A Ansari
    American Journal of Finance and Accounting 6 (1), 38-55 2019
    Citations: 3

  • Investor herding behaviour in the Indian equity market: Evidence from quantile regression
    A Ansari
    e-journal-First Pan IIT International Management Conference–2018 2020
    Citations: 1