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As a consequence of the convergence between manufacturing technology and the foundation technologies of Industry 4.0, it is becoming more important for firms to formulate an innovation strategy for their technological capabilities. In this context, the present study measures firm-level technology convergence (TC) capability using patent network analysis. A firm's TC capabilities are measured using three centrality indices pertaining to a patent network, which is constructed based on the relationship between patents and their international patent classification. For the empirical analysis, panel regression is conducted to observe the effect of TC capabilities on innovation for the top 30 firms in four manufacturing industries. We find that the TC degree positively influences the firms' overall innovation, namely their total number of patents, and negatively influences their convergent innovation, calculated as the ratio between the number of TC patents and the total number of patents, while the effect of TC betweenness is the opposite. These findings imply that while concentrating on similar technologies may promote quick technology application, it could hamper the enhancement of a TC's potential. To promote TC, a firm should thus develop technologies more likely to be involved in TC.

This study selects a case involving water purification systems in Binh Dinh, Vietnam, as an appropriate example to examine appropriate technology (AT) acceptance factors and derive possible insights into the stable settlement and development processes whereby to diffuse AT. This analysis administered questionnaires to users of water purification systems installed in five elementary and middle schools in Binh Dinh, from which 296 samples were collected for the final analysis. The original unified theory of acceptance and use of technology (UTAUT) was modified by incorporating the factors of physical support and educational support, and empirically studied using structural equation modeling. The findings revealed that all constructs significantly affect the behavioral intentions toward AT, of which performance expectancy and physical support have the most significant impact. Thus, understanding local needs and improving the quality of life by spreading AT are key in its acceptance and diffusion. Furthermore, sustainable technology is guaranteed only if human and economic support is accompanied by AT development that fits the local context and environment. Finally, the analysis results, that moderating effects differ by role, imply that educational support's influence varies between manager and student groups.

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