Umara Noreen

Umara Noreen

orcid

Research Focus & Metrics

Academic Career Length

13Years (2014-Present)

(Calculated once Scilit publication data is synced: current year − year of first publication + 1)

Representative Publications

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16 February 2023 in Sustainability
Verified
Journal Article
Open access
PDF file
UNUmara Noreen
Umara Noreen
ASAttayah Shafique
Attayah Shafique
ZAZaheer Ahmed
Zaheer Ahmed
MAMuhammad Ashfaq
Muhammad Ashfaq
The simulation of human intelligence in machines, called Artificial intelligence, has risen, and plays an important role in the new banking era. The present study aims to discuss the consumer’s perspective on artificial intelligence’s adoption in Asian countries. The questionnaire was developed and distributed to collect data from five Asian countries (Pakistan, China, Iran, Saudi Arabia, and Thailand). The total useable responses were 799. The results showed that the factors (awareness, attitude, subjective norms, perceived usefulness, and knowledge of artificial intelligence technology) had a significant and positive relationship with the intention to adopt AI in the banking sector. However, perceived risk shows a negative but significant relationship with the intentions to adopt AI. Overall, the findings of this study will be a worthy insight for making strategic decision-making in the banking industry. This will enable the banking management to build a strategy to increase the trust of consumers, which will help them to overcome risks and give them confidence in using digital technology while making transactions. The banking sector also focuses on innovative AI technologies to improve customer services as well as overall growth by generating more revenue.

18 June 2014 in Environmental Science and Pollution Research
Verified
Journal Article
Closed access
PDF file
FSFaiza Sajjad
Faiza Sajjad
UNUmara Noreen
Umara Noreen
Khalid ZamanKhalid Zaman
Khalid Zaman

24 March 2021 in Sustainability
Verified
Journal Article
Open access
PDF file
ASAsif Saeed
Asif Saeed
UNUmara Noreen
Umara Noreen
AAAkbar Azam
Akbar Azam
MTMuhammad Sohail Tahir
Muhammad Sohail Tahir
In today’s world, the energy sector is considered the backbone of any economy and plays a key role in carbon trading markets and mitigation actions. This study explores the impact of CSR governance on carbon footprints and the social performances of the energy sector. Using an international sample of 45 countries from 2002 to 2017, we find that the existence of a CSR committee improves the firm’s social responsibility and effectively mitigates the carbon footprint. Further, our results present that a large CSR committee with more experienced board members are effective to implement sustainable business practices. Furthermore, a CSR committee with experienced board members does not mitigate the environmental and social concerns, when energy firms have more powerful CEOs. Collectively, our evidence indicates that the existence of CSR governance is favorable to focus on social issues than environmental ones.

31 October 2020 in The Journal of Asian Finance, Economics and Business
Verified
Journal Article
Open access
NDNevi Danila
Nevi Danila
UNUmara Noreen
Umara Noreen
NANoor Azlinna Azizan
Noor Azlinna Azizan
MFMuhammad Farid
Muhammad Farid
ZAZaheer Ahmed
Zaheer Ahmed

30 November 2019 in The Journal of Asian Finance, Economics and Business
Verified
Journal Article
Open access
NQNoor Ul Qayyum
Noor Ul Qayyum
UNUmara Noreen
Umara Noreen

20 August 2020 in Sustainability
Verified
Journal Article
Open access
PDF file
UAUsman Ayub
Usman Ayub
SKSamaila Kausar
Samaila Kausar
UNUmara Noreen
Umara Noreen
MZMuhammad Zakaria
Muhammad Zakaria
IJImran Abbas Jadoon
Imran Abbas Jadoon
The importance of downside risk cannot be denied. In this study, we have replaced beta in the five-factor model of using downside beta and have added a momentum factor to suggest a new six-factor downside beta capital asset pricing model (CAPM). Two models are tested—a beta- and momentum-based six-factor model and a downside-beta- (proxy of downside risk) and momentum-based six-factor model. Beta and downside beta are highly correlated; therefore, portfolios are double-sorted to disentangle the correlation. Factor loadings, i.e., size, value, momentum, profitability, and investment, are constructed. The standard methodologies are applied. Data for sample stocks from different non-financial sectors listed in the Pakistan Stock Exchange (PSX) are taken from January 2000 to December 2018. The PSX-100 index and three-month T-bills are taken as proxies for market and risk-free returns. The study uses three subsamples for robustness—period of very high volatility, period of stability, and period of stability and growth with volatility. The results show that the value factor is redundant in both models. The momentum factor is rejected in the beta-based six-factor model only. The beta-based six-factor model shows very low R2 in periods of highly volatility. The R2 is high for the other periods. In contrast, the downside beta six-factor model captures the downside trend of the market in an effective manner with a relatively high R2. The risk–return relationship is stronger for the downside beta model. These reasons lead us to believe that, overall, the downside beta six-factor model is a better option for investors as compared to the beta-based six-factor model in the area of asset pricing models.