• Journal of Technology Innovation
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• v.31 no.2
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• pp.83-110
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• 2023

This study deals with the process by which 'Social problem-solving R&D model' is established in Korean society through the evolution of the government's R&D program. We will examine the process by which a 'Social problem-solving R&D model', which was not present in companies, science and technology communities, and civil society, is formed through government R&D programs. To this end, we present a conceptual framework to analyze the process of co-evolution of 'Social problem solving R&D model', the organizational community that supports and implements it, and the institutions that supports the new model. In the synthesis, policy measures to enhance 'Social problem-solving R&D model' are dealt with.

• Journal of Science and Technology Studies
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• v.18 no.3
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• pp.255-289
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• 2018

The social problem-solving R&D is different from the goal and process in comparison with research aimed at scientific excellence and industrial innovation. It pursues social values and active participation of the end-user civil society. In this study, we try to derive its characteristics by analyzing the cases that are evaluated as successful social problem solving R&D project. In order to analyse the social problem-solving R & D case, these four variables are selected; 1) social and technological planning for problem solving 2) participatory technological development 3) law, system and delivery system development for innovation deployment 4) scale-up of new R&D process. Those are important issues identified through case studies: 1) the tools and support services needed to carry out social and technical planning effectively, 2) the role of the Living Lab to coordinate opinions with experts and users, 3) the legislative and institutional improvement activities as important as technological development, 4) researcher's change through interaction with end user.

• Journal of Korea Society of Digital Industry and Information Management
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• v.17 no.4
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• pp.161-175
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• 2021

This study analyzed the efficiency and influence factors according to the main research institute type of R&D Program for the local community problem-solving. This study applied data envelopment analysis (DEA) method and Tobit regression analysis by using 20 institutions that participated in R&D Program. The results are summarized as follows. First, Analysis results according to the research institute type of R&D project, Efficient DMUs showed more regional innovation institutions than social economy enterprises. But regional innovation institutions were the lowest in the CCR and BCC model. However, efficiency dose not differ between regional innovation institutions and social economy enterprises. Second, as a result of the analysis relation between efficiency and allocation characteristics of R&D input, the participation of regional innovation organizations as participating organizations has a negative effect on efficiency. It was found that the higher the proportion of government subsidies and the higher the employment rate of the vulnerable, which is a social achievement, the positive effect on efficiency. The implication of this study is that the participation of social economy enterprises as the main R&D institution and government R&D support can provide social economy enterprises with opportunities to accumulate R&D capabilities and experience successful commercialization.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.4
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• pp.159-172
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• 2023

In general, social problem-solving research aims to create important social value by offering meaningful answers to various social pending issues using scientific technologies. Not surprisingly, however, although numerous and extensive research attempts have been made to alleviate the social problems and issues in nation-wide, we still have many important social challenges and works to be done. In order to facilitate the entire process of the social problem-solving research and maximize its efficacy, it is vital to clearly identify and grasp the important and pressing problems to be focused upon. It is understandable for the problem discovery step to be drastically improved if current social issues can be automatically identified from existing R&D resources such as technical reports and articles. This paper introduces a comprehensive dataset which is essential to build a machine learning model for automatically detecting the social problems and solutions in various national research reports. Initially, we collected a total of 700 research reports regarding social problems and issues. Through intensive annotation process, we built totally 24,022 sentences each of which possesses its own category or label closely related to social problem-solving such as problems, purposes, solutions, effects and so on. Furthermore, we implemented four sentence classification models based on various neural language models and conducted a series of performance experiments using our dataset. As a result of the experiment, the model fine-tuned to the KLUE-BERT pre-trained language model showed the best performance with an accuracy of 75.853% and an F1 score of 63.503%.

• Journal of Technology Innovation
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• v.7 no.2
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• pp.21-36
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• 1999

This paper presents a R&D investment model for Information and telecommunications (I&T) technology, which can be used by group decision makers, using multiple objective linear programming (MOLP). The MOLP model involves the simultaneous maximization of three linear objective functions associated with three criteria, which are social, technological, and economic criterion. This model is different from the traditional one which only involves the maximization of economic criterion. The presented problem in this model can be formulated as a problem of optimizing a linear function over an efficient set of MOLP. Its application to the National R&D Project in I&T Industry is also presented. In this application, the Analytic Hierarchy Process (AHP) is proposed to estimate the weights, which are used as the coefficients in each objective function of the MOLP model and in a linear decision function. By solving this problem, it yields a suitable R&D investment ratio to each technology field. It is showed that the MOLP model can be useful decision aid in formulating R&D investment plan in I&T industry which needs to be decided by group decision makers, not by an individual. It is expected that the MOLP model works as the basis for planning R&D investment strategy in I&T industry.