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Record W2597590713

Career Progression of Indian Women Bank Managers: An Integrated 3P Model

2016· article· en· W2597590713 on OpenAlexaboutno aff
Tania Saritova Rath, Madhuchhanda Mohanty, Bibhuti Bhusan Pradhan

Bibliographic record

VenueSouth Asian Journal of Management · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicBanking Sector Performance and Management
Canadian institutionsnot available
Fundersnot available
KeywordsPublic sectorPrivate sectorLiberalizationBusinessFinancial systemEconomicsEconomyEconomic growthMarket economy
DOInot available

Abstract

fetched live from OpenAlex

INTRODUCTIONThe Indian banking sector has seen exponential growth due to opening up of the economy in the 1990s through liberalization, privatization and globalization. This also led to an increase in scope of employment opportunities for women in the banking sector. When the Indian banking sector was nationalized in 1969, the development especially encouraged women to join banking jobs. The growth of private and foreign banks in 1990s also opened up newer employment opportunities for women. This sector has emerged as a major career option for Indian women. The banking sector in India is considered good for women because it is a source of respect, recognition, and is a safer sector to work (Srinivas, 1992; and Centre for Social Research, 2009). The total proportion of women employees in Banks has grown from 11 per cent (Bhatnagar, 1988) to 18 per cent (RBI, 2013) in last 3 decades. Women managers' strength has grown from 4 per cent (Bhatnagar, 1988) to 17 per cent (RBI, 2013). Public sector banks have 62 per cent of women managers, while private and foreign banks account for 38 per cent. State Bank of India (SBI), the major public sector bank has 13 per cent women managers, 31 per cent clerks and 20 per cent women employees overall (SBI, 2014). ICICI Bank, the major private sector bank had 25 per cent women employees as on March 2012 (RBI, 2013). The year 2013 can be regarded as a breakthrough year in Indian Banking Sector as SBI, the largest public sector commercial bank in the country, broke its 207-year tradition of having male CEOs, with Arundhati Bhattacharya becoming Chairman of the bank. This was followed by Usha Ananthasubramanian being named to chair the Bharatiya Mahila Bank (BMB). Thus, the number of CEOs in public sector banks became five, besides the private sector and foreign banks, a remarkable development in the banking sector in India (Mukherjee, 2013).The seemingly bright prospects for women managers in Indian banking sector prompted this research study with an aim to understand the factors that determine career progression of women managers in this sector. This is especially significant, when it is noted that an increase in women's education and participation in labor force has not led to significant representation of women in management jobs. The few women, who do make it to the top, make us believe that there is a sustainable change in the gender equations within corporations and businesses, which is not true (Centre for Social Research, 2009). The Gender Diversity Benchmark Report for Asia 2011 (published by Community Business) has highlighted the lowest percentage of labor force participation of women in India (Community Business, 2011). The representation of women in junior and middle-level management positions in India also continues to be lowest among major Asian countries, as well as in the world. The proportion of women leaving the job between junior to middle level is highest for India at 48 per cent, as compared to other major Asian countries (Community Business, 2011). Due to this, lesser number of women are available in the middle level to progress the senior positions. Over 60 per cent of women work in services sector globally (Statistical overview of women in the workforce, 2016). The labor force participation of women has decreased in India where as it is constantly growing in USA, Canada, Australia and in other developed countries. India's rate in this regard has fallen from 34 per cent in 1999-2000 to 27 per cent in 2011-12. But the Indian banking sector tells a different story. In the banking sector, women employees are constantly growing in numbers at the entry level, and this is also the sector that has recently witnessed women executives breaking the glass ceiling and reaching top positions. However, between the top and bottom of the organizational pyramid, the movement of women managers along the career ladder is not consistent and continuous. Thus, a research study on the phenomenon of career progression of women managers was deemed to be necessary. …

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How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.047
Threshold uncertainty score0.117

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.006
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0040.004
Science and technology studies0.0030.002
Scholarly communication0.0060.002
Open science0.0030.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0350.004

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.015
GPT teacher head0.221
Teacher spread0.206 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations5
Published2016
Admission routes1
Has abstractyes

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