AIMA witness 20 pc growth in registration for MAT entrance exam in 2023 over pre-Covid era
AIMA witness 20 pc growth in registration for MAT entrance exam in 2023 over pre-Covid era
Mumbai, All India Management Association, a federation of Local Management Associations , has witnessed a 20 per cent growth in registration for MAT in 2023 compared to the pre-Covid year.
MAT has actively expanded its test centers across the country, making the examination more accessible to aspiring candidates and increasing the number of locations where the test is conducted, eliminating geographical barriers, which allowed students from diverse regions to participate.
"This strategic expansion has undoubtedly contributed to the significant rise in the applicant count. MAT has seen a significant 20 per cent growth in candidate registrations post-Covid.
"There has been a rise in the number of women candidates registering for MAT. With 45 per cent of women candidates in 2023, there is a growth of approximately 3 per cent compared to 2019," AIMA Director Daljeet Singh told PTI.
There has also been a 3 per cent growth in registration by women candidates for MAT last year compared to 2019. The rise in popularity of MAT has led to an increasing number of registrations in tier II and III cities.
"Providing candidates from tier II and III cities an opportunity to pursue their management dream from B-Schools of choice has also played a part in increase in MAT popularity and registrations.
"There is more participation of candidates from smaller cities including Agra, Asansol, Aurangabad, Balasore, Bhilai, Darbhanga, Durg, Durgapur, Ernakulam, Erode, Salem among others," he said.
The growth was notable in southern states like Tamil Nadu , Karnataka , and Kerala , as well as in states like West Bengal , Uttar Pradesh , and Bihar .
Top B-Schools participation in MAT and acceptance of its score for MBA and PGDM admissions has further contributed significantly for surge in candidate registrations and MAT popularity, he added.
This article was generated from an automated news agency feed without modifications to text.
