Authors: Abdullah Al Ruhul, Shiwei Wang
Abstract: This study examines the relationship between Technology Transfer (TT) and Technology Upgrading (TU) in the context of Bangladesh's emerging electric vehicle (EV) industry, an early-stage sector in which technology transfer is widely proposed as a channel for building domestic manufacturing capability. Because primary survey data from Bangladeshi EV-sector firms are not yet available, the analysis is conducted on a 300-observation dataset simulated for statistical demonstration purposes, applying the complete quantitative workflow — descriptive statistics, reliability analysis, Pearson correlation, and simple linear regression — that a primary-data study of this relationship would follow. TT and TU are each measured on multi-item five-point Likert scales (four and five items, respectively) and combined into composite scores. Both scales show strong internal consistency (Cronbach's α = 0.858 for TT and 0.885 for TU). The composite TT and TU scores are strongly and positively correlated (r = 0.678, p < 0.001), and a simple linear regression indicates that TT is a significant predictor of TU (B = 0.659, SE = 0.041, t = 15.918, p < 0.001), explaining approximately 46.0% of the variance in TU (R² = 0.460). These results confirm that the analytic pipeline is correctly specified and ready to be applied to real industry data; they are reported as a methodological template rather than as evidence about Bangladesh's actual EV sector. The paper closes with a concrete sampling, instrumentation, and analytic design for the primary-data study that would be required to test the TT–TU relationship among real EV-sector firms. Data-status statement: All quantitative analyses in this manuscript use simulated observations for methodological demonstration. No result is presented as evidence from actual Bangladeshi EV-sector firms.
