Surbhi Sethi, Srishti Saxena and Manju Singh
The unexpected outbreak of COVID-19 has expedited the trend toward online education. To facilitate undisruptive learning, EdTech companies are continuously working on providing…
Abstract
Purpose
The unexpected outbreak of COVID-19 has expedited the trend toward online education. To facilitate undisruptive learning, EdTech companies are continuously working on providing solutions to restore teaching and learning practices. This has caused a significant behavioral shift of the investors in the EdTech market. This study aims to analyze the effects of Web Market Traffic on the increased number of investors funding an EdTech Company in the market.
Design/methodology/approach
By drawing on the multi-method web analytics approach, this study analyses the nexus between Web Market Traffic and Investor's Behavior in the US and India, proving the hypothesized relationship in the proposed Model using a data sample of 300 EdTech Players.
Findings
There is a significant difference between the investor's behavior in India and the US. This study shows that the investors in the US are more inclined towards investing in EdTech companies in comparison to India. The Results demonstrate that monthly visits of consumers and the number of acquisitions by players positively affect the investor's behavior, while bounce rates take a toll on the number of investors.
Practical implications
This Study suggests that EdTech investors in the US and India should harness Web Traffic to capture the EdTech market. Further, this study offers practical implications that EdTech players can use to attract potential investors and increase brand visibility by improving web market traffic parameters.
Originality/value
This paper's original contribution is to empirically shed light on the effects of web market traffic on the investor's behavior. The study emphasizes the quintessentiality of managing the bounce rates and monthly visits for an EdTech market to attract more investors and capital inflow that enhance brand visibility. The study found that the investors behave distinctly in the developed and emerging markets in the US and India.
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Surbhi Seema Sethi and Kanishk Jain
This study aims to explore the potential benefits of integrating Artificial Intelligence (AI) with Social Emotional Learning (SEL) in educational settings.
Abstract
Purpose
This study aims to explore the potential benefits of integrating Artificial Intelligence (AI) with Social Emotional Learning (SEL) in educational settings.
Design/methodology/approach
A systematic review of emerging AI technologies such as virtual reality, chatbots, sentiment analysis tools, gamification and wearable devices is conducted to assess their applicability in enhancing SEL.
Findings
AI technologies present opportunities for personalized support, increased engagement, empathy development and promotion of well-being within SEL frameworks.
Research limitations/implications
Future research should focus on addressing ethical concerns, fostering interdisciplinary collaborations, conducting longitudinal studies, promoting cultural sensitivity and developing robust ecosystems for AI in SEL.
Originality/value
This study contributes by outlining pathways for leveraging AI to create inclusive and supportive learning environments that nurture students' socio-emotional competencies, preparing them for success in a globally connected world.
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Surbhi Gupta, Arun Kumar Attree, Ranjana Thakur and Vishal Garg
This study aims to examine the role of Bilateral Investment Treaties (BITs) in attracting higher foreign direct investment (FDI) inflows into the major emerging economies namely…
Abstract
Purpose
This study aims to examine the role of Bilateral Investment Treaties (BITs) in attracting higher foreign direct investment (FDI) inflows into the major emerging economies namely Brazil, Russia, India, China and South Africa (BRICS) from the source developed, developing and other emerging economies over a period of 18 years from 2001 to 2018.
Design/methodology/approach
To estimate the results, panel data regression on a gravity-knowledge capital model has been used. To account for the problem of endogeneity we have used the two-step difference Generalised Method of Moments estimator proposed by Arellano and Bond (1991).
Findings
We find that contradictory to theory and expectations, BITs result in a fall in FDI inflows in BRICS economies. BITs ratified by BRICS economies are not able to provide a sound and secure investment environment to foreign investors, thereby discouraging FDI in these economies.
Originality/value
To the best of the authors’ knowledge, this study is the first to examine the impact of BITs on FDI inflows into the emerging BRICS economies. Further, the impact of BITs on FDI flows among developed nations, i.e. north-north FDI and from developed to developing countries, i.e. north-south FDI has already been studied by many researchers. But so far, no study has examined this impact on FDI among developing and emerging economies (south-south FDI), despite an increase in FDI flows among these economies. Therefore, this study seeks to overcome the limitations of previous studies and tries to find out the impact of BITs on FDI inflows in BRICS economies not only from source developed but also from source developing and other emerging economies.