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- P-ISSN2287-1608
- E-ISSN2287-1616
- KCI
ISSN : 2287-1608
Vol.6 No.1
Abstract
The essence of inclusive innovation is to serve poor, marginalized and underprivileged sections of society to improve their livelihoods and enable them to climb up the socio-economic ladder. In this article, we explore the contemporary Indian landscape. There is a diversity of institutions and institutional approaches, multiple methodologies and goals in promoting inclusive innovations in this landscape. There are grassroots innovation institutions. All these institutions and groups have demonstrated how to improve the living conditions of poor people and enhance their income. They have developed different methodologies of inclusive innovation to intervene, build capacities and capabilities of poor people towards bridging informal and formal sectors of economy. Indian landscape can now boast of some successful models and a “social laboratory” for inclusive innovation. The challenge, however, remains to replicate and multiply these models to impact other sectors of Indian informal economy.
Abstract
This study explores how the technology commercialization process leads to either success or failure after transfer from PROs to SMEs by conducting a binomial logistic regression analysis. We found that the more additional development a firm implements on the transferred technology, the more likely the commercialization is to fail. The higher number of alternative technology and bigger market risk are associated with a greater likelihood of failure. On the other hand, the existence of complementary technology, the degree of cooperation with the technology provider, the size of the target market, the willingness of the CEO, and the funding availability are known to have positive effects on the success of technology commercialization. In addition, the case studies we conducted from the sample companies demonstrated that “market uncertainty,” “technological issues depending on the technology-specific characteristics,” and “a lack of funding capability” are some of the causes for failure of technology commercialization.
Abstract
This study aims to analyze the factors that could influence business decisions of in the commercialization of R&D when technology is transferred from government research institutes (GRIs) to small and medium-sized enterprises (SMEs). We examine 353 such cases of technology transfer. The dependent variable is whether the licensee had the intention of following up with R&D after the technology has been transferred. The independent variables, classified into ex-ante factors and ex-post factors, consist of the involvement of SMEs into GRI R&D, technology readiness level, relatedness to existing technologies, and contribution to sales revenue and level-up of existing technologies. The results of the study show that the contribution to existing technologies has a positive impact on R&D commercialization. However, unlike our expectation, contribution to sales revenue, the involvement of SMEs into GRI R&D, technology readiness level, the relatedness to existing technologies of the technology transferred have no impact on follow-up R&D.
Abstract
This article aims at demonstrating location specific approach for agricultural technology promotion and adoption in improving the livelihood of the small farmers in the haor basin and coastal belt of Bangladesh. Innovative technologies that have potentials are initially screened by ex-ante investigation and instrumented by the business model canvas, which is used as a bottom-up approach for sustainability of the adoption of proposed technology innovations. Village-level extension farmers, sub-district extension officers and farmers’ cooperative are the unique and central features to the business models and forward linkages. Extension service, power tiller, low-lift pump, sunflower, shallow tube well, quality seed, forward linkage for farmed duck eggs, live ducks and open catch fish etc. are the suggested potential technology innovations for the small farmers. The technology adoption business model can be reinvented for different locations within or beyond the country considering the local agricultural problems and prospects for greater sustainability.
Abstract
This paper focuses on the relationship between the characteristics of network and the productivity of scientists, which is rarely examined in previous studies. Utilizing a unique dataset from the Korean Citation Index (KCI), we examine the overall characteristics of the research network (e.g. distribution of nodes, density and mean distance), and analyze whether the network centrality is related to the scientific productivity. According to the results, firstly we have found that the collaborative research network of the Korean academics in the field of statistics and computer science is a scale-free network. Secondly, these research networks show a disciplinary difference. The network of statisticians is denser than that of computer scientists. In addition, computer scientists are located in a fragmented network compared to statisticians. Thirdly, with regard to the relationship between the researchers’ network position and scientific productivity, a significant relation and their disciplinary difference have been observed. In particular, the degree centrality is the strongest predictor for the scientists’ productivity. Based on these findings, some policy implications are put forward.
Abstract
This paper approaches knowledge capital as social infrastructure and analyzes its impact on economic growth. To this end, we constructed a panel dataset for 120 countries for the years 2000-2014 and estimated the economic growth function using the panel analysis. As proxies for knowledge capital, we used the R&D expenditure per capita and the number of patent applications per thousand people in each country, both measured in stock. Economic growth was measured in terms of real GDP per capita and real value added per capita at the industry level. The empirical findings demonstrate that knowledge capital accumulated in a society significantly promotes economic growth. Especially R&D stock increases real value added per capita in all industries-not only manufacturing, but also services and agriculture-implying substantial inter-industry spillover effects. The findings of this study suggest that knowledge capital boosts economic growth as core social infrastructure.