A Dynamic Capability Framework for Sustainable Competitive Advantage in Firms

Thesis Abstract

In rapidly evolving and fiercely competitive markets, firms struggle to sustain advantageous positions due to cognitive limits, dynamic market conditions, and heterogeneous resource implications; this study investigates how a dynamic capability framework can operationalize and sustain competitive advantage through sensing, seizing, and reconfiguring capabilities. The problem addressed is the inadequacy of static resource-based explanations to account for performance resilience amid discontinuous environmental shifts, digital disruption, and global value chain realignments. The aim is to develop and validate a dynamic capability framework that integrates sensing, learning, reconfiguration, and governance mechanisms to generate sustainable competitive advantage. The specific objectives are (1) to identify the core dynamic capabilities that enable firms to sense opportunities and threats, to seize them through strategic alignment and resource orchestration, and to reconfigure organizational structures and processes; (2) to examine the moderating roles of organizational culture, leadership, and information technology maturity on the effectiveness of these capabilities; (3) to quantify the relationship between dynamic capabilities and sustained superior performance across product, process, and market dimensions; (4) to develop a parsimonious conceptual model and provide actionable prescription for firms operating in manufacturing and services sectors under high-velocity environments; and (5) to test the model in diverse institutional contexts to assess cross-country generalizability. The methodology adopts a mixed-methods design grounded in the dynamic capabilities perspective and supported by the absorptive capacity theory. The study samples 340 mid-to-large firms across manufacturing and service sectors in three economically distinct regions, employing stratified random sampling to ensure representation by firm size, sector, and corporate governance structure. Data collection comprises a structured survey instrument administered to senior managers (e.g., CEOs, COOs, strategy directors) and in-depth semi-structured interviews with 40 senior executives to capture nuanced capabilities and governance processes. The survey instrument includes validated scales for dynamic sensing, opportunity seizing, organizational reconfiguration, IT maturity, organizational culture, leadership style, and performance outcomes over a three-year horizon. Secondary data on firm performance is extracted from annual reports and financial databases to corroborate self-reported measures. Validity and reliability are ensured through pilot testing, confirmatory factor analysis, and Cronbach’s alpha assessments above 0.80. Analytical techniques include partial least squares structural equation modeling (PLS-SEM) to test the proposed measurement and structural models, multigroup analysis to explore contextual differences, and hierarchical regression to assess moderation effects. The qualitative component employs thematic analysis of interview transcripts, guided by the integrated framework of dynamic capabilities and learning organization theory, to triangulate quantitative findings and illuminate contextual mechanisms. Model specification integrates sensing–seizing–reconfiguring pathways with governance and IT maturity as antecedents and performance as the outcome, controlling for firm age, size, and industry. Robustness checks include alternative model specifications, cross-validation with holdout samples, and sensitivity analyses to account for common method bias. Key expected findings include (a) a positively significant path from dynamic sensing and seizing capabilities to strategic reconfiguration, mediated by learning and knowledge integration; (b) a strong direct effect of organizational IT maturity and aligned leadership on the efficiency of capability deployment; (c) cultural factors and governance mechanisms moderating the strength of the dynamic capabilities–performance link, with high-velocity environments amplifying effects; and (d) evidence of sectoral differences, with services firms benefiting more from agile reconfiguration while manufacturing firms leverage stronger sensing driven by digital twins and data analytics. The study contributes to knowledge by refining the dynamic capabilities framework with explicit governance and IT maturity constructs, providing a validated model that explicates the mechanisms by which firms achieve sustainable competitive advantage in volatile settings. It informs managers about the sequence and dependencies among sensing, seizing, and reconfiguring activities, and highlights organizational design and leadership practices that enhance resilience. Recommendations include investing in data-driven decision ecosystems, fostering learning-oriented culture, and developing modular organizational structures that enable rapid reconfiguration without compromising governance integrity. The main conclusion is that sustainable competitive advantage emerges from an integrated dynamic capability system where sensing, seizing, and reconfiguring are continuously orchestrated through mature IT capabilities and adaptive leadership, underpinned by a culture that endorses experimentation and disciplined risk management.