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Enregistrement W2597590713

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

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

Notice bibliographique

RevueSouth Asian Journal of Management · 2016
Typearticle
Langueen
DomaineBusiness, Management and Accounting
ThématiqueBanking Sector Performance and Management
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPublic sectorPrivate sectorLiberalizationBusinessFinancial systemEconomicsEconomyEconomic growthMarket economy
DOInon disponible

Résumé

récupéré en direct d'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. …

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,004
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Qualitatif · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,047
Score d'incertitude au seuil0,117

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0040,006
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,002
Bibliométrie0,0040,004
Études des sciences et des technologies0,0030,002
Communication savante0,0060,002
Science ouverte0,0030,003
Intégrité de la recherche0,0020,003
Charge utile insuffisante (le modèle a refusé de juger)0,0350,004

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,015
Tête enseignante GPT0,221
Écart entre enseignants0,206 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeQualitatif
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations5
Publié2016
Routes d'admission1
Résumé présentoui

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