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Opportunity Identification Capabilities: The Interpretive Sensing Dynamic Capability for Sustainable Manufacturing in Kenya

Domaine:

socioeconomic

Type de record:

paper
Créateur:
Fri
Éditeur:
Elsevier BV
Hôte:
Kenya's large manufacturing firms face a defining strategic inflection point. Mounting ESG pressures, tightening regulatory enforcement, and unprecedented structural opportunities such as AfCFTA market access and the green manufacturing transition require not only detecting environmental signals but correctly interpreting them as actionable opportunities (Kenya Association of Manufacturers [KAM], 2025; Sustainable Energy for All [SEforALL], 2025). This paper conceptualizes opportunity identification as the interpretive sensing microfoundation within the Dynamic Capabilities View (DCV), positioned as the second distinct component of sensing. This capability builds on, but is analytically separate from, environmental scanning or signal detection (Teece, 2007). Through synthesis of recent empirical work (2022-2026) on dynamic capabilities, opportunity recognition, green dynamic capabilities, and Kenyan manufacturing performance, the paper argues that large KAM-registered firms require structured organizational routines for pattern recognition, prior knowledge mobilization, and cross-functional interpretation of ESG-relevant signals-not merely their detection (Harvey, 2022; Gudetu et al., 2024; Limo et al., 2025). Extant Kenyan scholarship remains biased toward SMEs and focuses predominantly on scanning or detection, leaving the cognitive-interpretive dimension of sensing underexplored in large firms (Orwa et al., 2026; Rono et al., 2021). Validated sensing capabilities scales reveal four distinct components; analytical processes, market intelligence mobilization, business experience, and organizational articulation. Opportunity interpretation through experience and articulation remains under-explored (Repositório ISCTE-IUL, n.d.; Gudetu et al., 2024). Recommendations are provided for large Kenyan manufacturers to institutionalize structured interpretation routines that convert ESG signals into identified green, circular-economy, and trade-related opportunities, thereby operationalizing opportunity identification as a foundational sustainable dynamic capability (Weber et al., 2025; KAM, 2025).

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Kam

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