Knowledge Management Practices and Organisational Performance in Indian IT Services Firms
Author(s): Anitha Ramachandran, David O. Harrington
Affiliation: Faculty of Business and Economics, University of Melbourne, Melbourne, Victoria, Australia
Page No: 78-82-
Volume issue & Publishing Year: Volume 3, Issue 3, 2026/03/22
Journal: International Journal of Modern Engineering and Management | IJMEM
ISSN NO: 3048-8230
DOI:
Abstract:
Knowledge management (KM) — the systematic creation, capture, sharing, and application of organisational knowledge — is foundational to competitive advantage in the IT services industry, where intellectual capital constitutes the primary input and project delivery excellence the primary output of value creation. India's IT services sector, which generated USD 245 billion in revenue in FY2023-24 according to NASSCOM and employs 5.4 million professionals, operates in an environment of accelerating knowledge obsolescence: the average half-life of relevant software development knowledge has declined from 4.2 years (2010 estimate) to 2.1 years (2024 estimate) as cloud architecture, AI integration, and cybersecurity threat landscapes evolve at unprecedented velocity. This study examines KM practice maturity and its performance consequences across 178 India-headquartered IT services firms, using a mixed-methods design combining KM maturity assessment surveys with firm-level financial and operational performance data from NASSCOM's proprietary benchmarking database (2017-2024). KM maturity is operationalised across six practice dimensions — knowledge creation, codification, storage, sharing, application, and measurement — using an adapted Knowledge Management Maturity Model (KMMM). Structural Equation Modelling reveals that KM maturity significantly predicts project delivery performance (β=0.54, p<0.001), employee retention (β=0.41, p<0.001), and revenue per employee (β=0.38, p<0.001). Communities of practice (CoP) adoption emerges as the strongest individual KM mechanism (β=0.49), followed by systematic mentoring programmes (β=0.44) and AI-enabled knowledge discovery tools (β=0.37). Firm size moderates the KM-performance relationship: mid-size firms (5,000-25,000 employees) exhibit the strongest KM maturity-performance coupling, while large firms show attenuated relationships attributable to coordination complexity, and small firms show weaker relationships due to resource constraints in formal KM system investment.
Keywords:
knowledge management, IT services, NASSCOM, communities of practice, knowledge maturity model, SEM, mentoring, employee retention, India, organisational performance
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