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Career Decisions of Indian Female Talent: Implications for Gender-sensitive Talent Management
(2020)
Purpose: Talent scarcity in emerging economies such as India poses challenges for companies,and limited labour market participation among well-educated women has been observed. The reasons that professionals decide not to pursue a further corporate career remain unclear. By investigating career decision making, this article aims to highlight (1) the contextual factors that impact those decisions, (2) individuals’ agency to handle them, and (3) the implications for talent management (TM).
Design/methodology/approach: Following a qualitative research design, computer-aided analysis was conducted on interviews with 24 internationally experienced Indian business professionals. A novel application of neo-institutionalism in the Indian context was combined with the family-relatedness of work decisions (FRWD) model.
Findings: Career decisions indicate that rebellion against Indian societal and family expectations is essential to following a career path, especially for women. TM as part of the current institutional framework serves as a legitimising façade veiling traditional practices that hinder females’ careers.
Research limitations: Interviewees adopted a retrospective perspective when describing their career decisions; therefore, different views might have existed at the moment of decision making.
Practical implications: Design and implementation of gender-sensitive TM adjusted to fit the specific Indian context can contribute to retaining female talent in companies and the labour market.
Originality/value: The importance of gender-sensitive TM can be concluded from an empirical study of the context-based career decision making of experienced business professionals from India. The synthesis of neo-institutionalism, the FRWD model and the research results provides assistance in mapping talent experiences and implications for overcoming the challenges of talent scarcity in India.
HRM processes are increasingly AI-driven, and HRM supports the general digital transformation of companies’ viable competitiveness. This paper points out possible positive and negative effects on HRM, workplaces, and workersorganizations along the HR processes and its potential for competitive advantage in regard to managerial decisions on AI implementation regarding augmentation and automation of work.
A systematic literature review that includes 62 international journals across different disciplines and contains top-tier academic and German practitioner journals was conducted. The literature analysis applies the resource-based view (RBV) as a lens through which to explore AI-driven HRM as a potential source of organizational capabilities.
The analysis shows four ambiguities for AI-driven HRM that might support sustainable company development or might prevent AI application: job design, transparency, performance and data ambiguity. A limited scholarly discussion with very few empirical studies can be stated. To date, research has mainly focused on HRM in general, recruiting, and HR analytics in particular.
The four ambiguities’ context-specific potential for capability building in firms is indicated, and research avenues are developed.
This paper critically explores AI-driven HRM and structures context-specific potential for capability building along four ambiguities that must be addressed by HRM to strategically contribute to an organization’s competitive advantage.