BLOCKCHAIN ADOPTION AND ORGANIZATIONAL LONG-TERM GROWTH IN SMALL AND MEDIUM ENTERPRISES (SMES)

Abstract

This study addresses the problem that small and medium enterprises (SMEs) often lack quantitative evidence on whether deeper blockchain use, beyond awareness or pilot trials, is associated with sustained organizational growth and which readiness conditions enable adoption. The purpose was to test a Technology-Organization-Environment (TOE) model in which technological readiness, organizational readiness, and environmental pressure predict blockchain adoption intensity, and adoption intensity predicts a multidimensional long-term growth index. Using a quantitative, cross-sectional, case-based survey design, data were obtained from 220 SME enterprise cases spanning manufacturing (29.1%), retail/wholesale (25.0%), services (34.5%), and logistics/other sectors (11.4%). Most firms employed 10-49 staff (52.7%) in the case setting, and 34.1% reported active blockchain use in at least one business process. Key variables were measured on five-point Likert scales and showed strong internal consistency (Cronbach’s alpha: technological readiness = .86, organizational readiness = .88, environmental pressure = .82, adoption intensity = .90, and long-term growth = .89). The analysis plan applied descriptive statistics, Pearson correlations, and two-stage multiple regression, controlling for firm size, firm age, and sector. Descriptively, perceptions were moderate to high (technological readiness M = 3.74, SD = 0.63; adoption intensity M = 3.42, SD = 0.72; long-term growth M = 3.68, SD = 0.60), and operational efficiency was the highest growth dimension (M = 3.82, SD = 0.64). Adoption intensity correlated with long-term growth (r = 0.56, p < .01) and with TOE determinants (r = 0.49 with technological readiness, r = 0.52 with organizational readiness, and r = 0.41 with environmental pressure, all p < .01). In regression Model A, TOE determinants explained 42.1% of adoption-intensity variance (R² = 0.421; F(3,216) = 52.34, p < .001), with organizational readiness the strongest predictor (β = 0.34, p < .001), followed by technological readiness (β = 0.27, p < .001) and environmental pressure (β = 0.19, p = .001). In Model B, adoption intensity predicted long-term growth net of controls (R² = 0.420; F(5,214) = 31.08, p < .001), with a strong positive effect for adoption intensity (β = 0.49, p < .001) and a small effect for firm size (β = 0.12, p = .036), while firm age and sector were not significant. Supplementary models showed that adoption intensity was especially linked with operational efficiency (β = 0.51, p < .001) and innovation capability (β = 0.44, p < .001). Implications are that SMEs should treat blockchain as a governed capability-building program and prioritize managerial commitment, IT capability, and process readiness, because deeper routinized integration is associated with stronger growth outcomes through operational and innovation pathways.