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Various institutions such as universities and corporations strive to commercialize technologies produced through R&D investment. The ideal way to commercialize technology is to transfer it, recognizing the value of the developed technology. Technology transfer is the transfer of technology from R&D entities, such as universities, research institutes, and companies, to others, with the advantage of spreading research results and maximizing cost efficiency. In other words, if enough technology is transferred, it can be commercialized. Although many institutions have various support measures to assist in transferring technology, there is no substitution for quantitative, objective methods. To solve this problem, this paper proposes a technology transfer prediction model based on the information found in patents. However, it is not realistic to include the information from all patents in the quantitative, objective method, so patterns related to technology transfer must be identified to select the appropriate patents that can be used in the predictive model. In addition, a method is needed to address the insufficient training data for the model. Training data are limited because some technology transfer information is not disclosed, and there is little technology transferred in new technology fields. The technology transfer prediction model proposed in this paper searches for hidden patterns related to technology transfer by imaging the patent information, which can also be applied to image analysis models. Furthermore, augmenting the data can solve the problem of the lack of learning data for technology transfer. To examine whether the proposed model can be used in real industries, we collected patents related to artificial intelligence technology registered in the United States and conducted experiments. The experimental results show that the models trained by imaging patent information performed excellently. Moreover, it was shown that the data augmentation technique can be used when there are insufficient data for technology transfer. [ABSTRACT FROM AUTHOR]

Hip-hop has evolved from a social and musical niche to a mass phenomenon and a key element of American pop culture with a global reach. Meanwhile, rap music and hip-hop culture are also a commercial success story in which the materialistic American Dream has once again come true. How did this former ghetto phenomenon become today's marketplace icon, whose once marginalized performers are now pampered by luxury brands and work as successful businesspeople and investors? Drawing on previous research on youth and subcultures and introducing the concept of "mainstream subculture," this paper outlines the development and commercialization of American hip-hop culture over four decades from 1979 to 2019. Ongoing discussions about the preservation of urban authenticity and concerns about a (sub-)culture "selling out" are also taken into account. The article concludes with a prognosis for the future of hip-hop culture and the industry in the United States. [ABSTRACT FROM AUTHOR]

Renewable jet fuel (RJF) production has been recognized as a promising approach for reducing the aviation sector's carbon footprint. Over the last decade, the commercial production of RJF has piqued the interest of airlines and governments around the world. However, RJF production can be challenging due to its dispersed supply resources. Furthermore, the production of RJF is more costly compared to producing conventional jet fuel. In this study, using a mixed integer linear programming (MILP), we design a corn-stover-based RJF supply chain network in which we obtain an optimized configuration of the supply chain and determine operational decisions required to meet RJF demand at airports. To accelerate the commercialization of RJF production, we examined four incentive programs designed to cover the supply chain's costs, with agricultural statistics districts serving as the designated supply regions. This study is validated by employing the model to design the supply chain in the Midwestern United States. The results from this study are promising as they show the supply chain can achieve commercialization with partial financial coverage from the incentive programs. Based on the findings of this study, policymakers can devise policies to commercialize RJF production and accelerate its adoption by the industry. [ABSTRACT FROM AUTHOR]

Previous studies have found that commercialized nonprofits may be less likely to offer free access to programs and services. This study draws on theoretical insights from the literature on nonprofit efficiency, the principal-agent problem, and nonprofit professionalism, going a step further to examine when commercialization leads to the exclusion of those unable to pay. Studying performing arts nonprofits in the United States from 2008 to 2016, the results suggest that the observed negative effects of commercialization on free access are not due to commercialized nonprofit leaders leaning towards efficiency through a cost-benefit mentality or pursuing their interests, but due partially to commercialized nonprofits moving toward professionalism. The findings have important implications for nonprofit professionalization, co-creation, and revenue portfolio management. [ABSTRACT FROM AUTHOR]