Khanal, Amir (2026) Data-Driven Decision Making and Strategic Performance in Nepalese SMEs: A Digital Transformation Perspective. Masters thesis, York St John University.

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Abstract

Small and Medium-sized Enterprises (SMEs) are the backbone of the economy of Nepal as they provide 22 per cent of GDP and 60 per cent of non-agricultural employment. While the Government's Digital Nepal Framework (Government of Nepal, 2019) has been introduced and digital infrastructure is improving with time, systematic data-driven decision making (DDDM) is still developing and unevenly distributed in the small and medium sized enterprises. In this study, the relationship between DDDM adoption and strategic performance of SMEs in Nepal is studied along with how digital capabilities, institutional barriers, and the adoption of Artificial Intelligence influence this relationship.
The study tests four hypotheses and is designed as a sequential explanatory mixed methods study, informed by Digital Transformation Theory (Vial, 2019) and supplemented by the theories of dynamic capabilities (Teece, Pisano and Shuen, 1997), absorptive capacity theory (Cohen and Levinthal, 1990) and institutional theory (North, 1990). IBM SPSS Statistics 29 and SmartPLS 4 (Partial Least Squares Structural Equation Modelling (PLS-SEM)) were used to analyse the quantitative survey that was conducted with n = 86 Nepalese SME managers and owners. Sixteen semi-structured interviews were then held with those who had agreed and analysed through Braun and Clarke's (2006) 6-phase reflexive thematic analysis in NVivo 14.
The model accounted for 55.7% of the variance in strategic performance. The hypothesized positive relationship between DDDM adoption and strategic performance (Digital Transformation Theory's main performance proposition) was supported first time in the context of a developing economy SME (β = 0.559, t = 3.335, p = 0.001, f² = 0.206). For H2 (digital capabilities mediation), the highly significant a path (β = 0.796, p < .001) was not matched by a path leading to the b path (BCa CI [−0.045, 0.408]), suggesting that capability development is progressing but that capabilities are not yet directly translating into performance in isolation. The institutional barriers moderation did not show statistical support (β = −0.117, p = 0.198), but a negative direction was theoretically appropriate. H4 — Moderation of AI adoption — was not supported (β = 0.003, p = 0.977) as the pre-adoption landscape of AI in the sample was moderate (M = 2.593).
The results of the thematic analysis led to five themes: DDDM as an emerging but fragmented practice; digital capabilities as the critical bottleneck; institutional barriers as geographically differentiated structural constraints; awareness of AI but no operational use; and — as an emergent theme — managerial digital orientation as an individual-level antecedent of DDDM adoption. This fifth theme is the most innovative theoretical perspective offered by the study, since it provides a new micro-foundational mechanism that is not covered in Digital Transformation Theory.
The study theoretically confirms the cross-contextual applicability of DTT, sets the boundary conditions for the digital capabilities mediation mechanism, and empirically documents the pre-adoption baseline of AI, while also proposing managerial digital orientation as a potential for theoretical integration in DTT's architecture. Practical implications are discussed for Nepalese SME managers, FNCCI, CNI, and the Government of Nepal, among which human capital development, geographic equity in investment in digital infrastructure, and sequencing of digital transformation policy are highlighted.

Item Type:	Thesis (Masters)
Status:	Published
Subjects:	A General Works > AC Collections. Series. Collected works A General Works > AI Indexes (General)
School/Department:	London Campus
URI:	https://ray.yorksj.ac.uk/id/eprint/15843

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