检索结果-内蒙古大学图书馆

TechRxiv 2022年

作者： He, Youwei Lee, Jeong-Dong Jeong, Dawoon Choi, Sungjun Kim, Jiyong Technology Management Economics and Policy Program Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Integrated Major in Smart City Global Convergence Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of

This study proposes an effective method to predict the development of technology from an evolutionary perspective. Product evolution is the result of technological evolution and market selection. A phylogenetic network is the main method to study product evolution. The formation of the dominant design determines the trajectory of technology development. How to predict future dominant design has become a key issue in technology forecasting and new product development. This study uses machine learning methods, combined with product evolutionary theory, and constructs a Fully Connected Phylogenetic Network dataset to effectively predict the future dominant design. © 2022, CC BY.

关键词： Forecasting

来源：评论

学校读者我要写书评

暂无评论

R & D partner type, product life-cycle, and innovation performance of high-technology ventures 2

R & D partner type, product life-cycle, and innovation perfo...

引用

2nd Annual IEEE International Symposium on Innovation and Entrepreneurship of the IEEE technology and Engineering management Society, TEMS-ISIE 2019

作者： Kim, Giwon M. Hwang, Juneseok Seoul National University Technology Management Economics and Policy Program Seoul Korea Republic of

ISBN: (纸本)9781728104355

To cope with rapidly changing market demand and deficiency of internal resources, innovative ventures actively invite various types of external partners to their innovation process. Although many research has been conducted to identify the effect of RD partner types on firm performances, few studies have taken into account venture firm as well as the stage of the product life-cycle in examining the issue, which can significantly affect the strategic decision on and the outcome of RD collaboration. To this end, this study focuses on high-technology ventures at three different stages in product life-cycle and examines the effect of RD collaboration with five different types of RD partner on innovation performance of ventures. Our findings reveal that for ventures in the introduction stage, RD collaboration with large firm is positively related to their innovation performance. In the growth stage of product life-cycle, RD collaborations with university, public research institute (PRI), and large firm are positively associated with innovation performance. Lastly, for ventures in the mature stage of product life-cycle, university and public research institute are suggested as effective partners for innovation performance of ventures. Neither RD collaboration with private research centers (PRC) nor other SMEs and ventures show a significant effect on innovation performance at all three stages of product life-cycle. This research contributes to the existing literature of open innovation and innovation management of ventures. © 2019 IEEE.

关键词： Life cycle

来源：评论

学校读者我要写书评

暂无评论

Guidance on the use of complex systems models for economic evaluations of public health interventions

引用

HEALTH economics 2023年第7期32卷 1603-1625页

作者： Breeze, Penny R. Squires, Hazel Ennis, Kate Meier, Petra Hayes, Kate Lomax, Nik Shiell, Alan Kee, Frank de Vocht, Frank O'Flaherty, Martin Gilbert, Nigel Purshouse, Robin Robinson, Stewart Dodd, Peter J. Strong, Mark Paisley, Suzy Smith, Richard Briggs, Andrew Shahab, Lion Occhipinti, Jo-An Lawson, Kenny Bayley, Thomas Smith, Robert Boyd, Jennifer Kadirkamanathan, Visakan Cookson, Richard Hernandez-Alava, Monica Jackson, Christopher H. Karapici, Amanda Sassi, Franco Scarborough, Peter Siebert, Uwe Silverman, Eric Vale, Luke Walsh, Cathal Brennan, Alan School of Health and Related Research University of Sheffield Sheffield UK British Medical Journal Technology Appraisal Group London UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Scotland UK School of Geography University of Leeds Leeds UK Department of Public Health LaTrobe University Melbourne Australia Centre for Public Health Queen's University Belfast Belfast UK Population Health Sciences Bristol Medical School University of Bristol Bristol UK NIHR Applied Research Collaboration West (ARC West) Bristol UK Department of Public Health Policy and Systems University of Liverpool Liverpool UK CRESS University of Surrey Guildford UK Department of Automatic Control and Systems Engineering University of Sheffield Sheffield UK Business School University of Newcastle Newcastle UK Lumanity-HEOR South Yorkshire Sheffield UK College of Medicine and Health University of Exeter Exeter UK London School of Hygiene & Tropical Medicine London UK Department of Behavioural Science and Health UCL London UK Brain and Mind Centre University of Sydney New South Wales Camperdown Australia United Kingdom Health Security Agency Birmingham UK MRC/CSO Social and Public Health Sciences Unit University of Glasgow Glasgow UK Centre for Health Economics University of York Heslington UK MRC Biostatistics Unit University of Cambridge Cambridge UK NIHR SPHR London School of Hygiene and Tropical Medicine London UK Centre for Health Economics & Policy Innovation Imperial College Business School London UK Nuffield Department of Population Health University of Oxford Oxfordshire Oxford UK Department of Public Health Health Services Research and Health Technology Assessment UMIT TIROL - University for Health Sciences and Technology Hall in Tirol Tyrol Austria Division of Health Technology Assessment and Bioinformatics ONCOTYROL - Center for Personalized Cancer Medicine Innsbruck Austria Center for Health Decision Science Departments of Epidemio

To help health economic modelers respond to demands for greater use of complex systems models in public health. To propose identifiable features of such models and support researchers to plan public health modeling projects using these models. A working group of experts in complex systems modeling and economic evaluation was brought together to develop and jointly write guidance for the use of complex systems models for health economic analysis. The content of workshops was informed by a scoping review. A public health complex systems model for economic evaluation is defined as a quantitative, dynamic, non-linear model that incorporates feedback and interactions among model elements, in order to capture emergent outcomes and estimate health, economic and potentially other consequences to inform public policies. The guidance covers: when complex systems modeling is needed;principles for designing a complex systems model;and how to choose an appropriate modeling technique. This paper provides a definition to identify and characterize complex systems models for economic evaluations and proposes guidance on key aspects of the process for health economics analysis. This document will support the development of complex systems models, with impact on public health systems policy and decision making.

关键词： complex systems economic modeling public health

来源：评论

学校读者我要写书评

暂无评论

A Robotic Dating Coaching System Leveraging Online Communities Posts

A Robotic Dating Coaching System Leveraging Online Communiti...

引用

International Conference on Electronics, Information and Communications (ICEIC)

作者： Sihyeon Jo Donghwi Jung Keonwoo Kim Eun Gyo Joung Giulia Nespoli Seungryong Yoo Minseob So Seung-Woo Seo Seong-Woo Kim Seoul National University Seoul South Korea Technology Management Economics and Policy Program Seoul National University Seoul South Korea Graduate School of Engineering Practice Seoul National University Seoul South Korea

ISBN: (数字)9781728191614

ISBN: (纸本)9781728191621

Can a robot be a personal dating coach? Even with the increasing amount of conversational data on the internet, the implementation of conversational robots remains a challenge. In particular, a detailed and professional counseling log is expensive and not publicly accessible. In this paper, we develop a robot dating coaching system leveraging corpus from online communities. We examine people's perceptions of the dating coaching robot with a dialogue module. 97 participants joined to have a conversation with the robot, and 30 of them evaluated the robot. The results indicate that participants thought the robot could become a dating coach while considering the robot is entertaining rather than helpful.

关键词： Employee welfare Entertainment industry Chatbot Robots

来源：评论

学校读者我要写书评

暂无评论

A Recurrence Plot-Based Graph Convolutional Network for Time Series Classification

SSRN

引用

SSRN 2024年

作者： Lee, Junghye Kang, Hyewon Lee, Taek-Ho Department of Intelligent Precision Healthcare Convergence Sungkyunkwan University 2066 Seobu-ro Jangan-gu Gyeonggi-do Suwon-si16419 Korea Republic of Technology Management Economics and Policy Program Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Institute of Engineering Research Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of Graduate School of Engineering Practice Seoul National University 1 Gwanak-ro Gwanak-gu Seoul08826 Korea Republic of

Over the past decades, time series classification (TSC) has become an essential task in many fields, leading to a plethora of TSC deep learning algorithms. The effectiveness of these algorithms largely depends on the quality of input representations. Among various representations, a recurrence plot (RP), a binary-encoded matrix, stands out as a powerful input representation. The RP encapsulates a topological recurrence, the unique property of time series data. This property is characterized by the fact that each point in a certain region of its phase space returns arbitrarily close to its initial position infinitely often. Despite its grid-like appearance, the essential information of the RP lies in its inherently intricate topological recurrence patterns. Recently, the RP has been widely used with a convolutional neural network (CNN) for TSC, treating the RP as grid-like data. However, the topological recurrence patterns can often be overlooked when using CNNs with their 2D convolution operation designed for Euclidean space. In this study, we propose an approach named RP-GCN that combines the RP with a graph convolutional network (GCN) to exploit the topological recurrence inherent in the RP, thereby improving TSC performance. Our RP-GCN transforms a multivariate time series into state matrices and RPs, redefining them as node feature matrices and adjacency matrices, respectively. We validated the performance of our RP-GCN on 35 benchmark multivariate time series classification datasets and found that it exhibited promising performance in terms of accuracy and inference time. © 2024, The Authors. All rights reserved.

关键词： Convolution

来源：评论

学校读者我要写书评

暂无评论

Factors that affect the technological transition of firms toward the industry 4.0 technologies

arXiv

引用

arXiv 2022年

作者： Kim, Seung Hwan Jeon, Jeong hwan Aridi, Anwar Jun, Bogang Technology Management Economics and Policy Program Seoul National University Seoul Korea Republic of Department of Electrical Engineering Ulsan National Institute of Science and Technology Ulsan Korea Republic of Graduate School of Artificial Intelligence Ulsan National Institute of Science and Technology Ulsan Korea Republic of Finance Competitiveness and Innovation Global Practice Europe and Central Asia Unit The World Bank Group Department of Economics Inha University Korea Republic of Department of Data Science Inha University Korea Republic of Research Center for Small Businesses Ecosystem Inha University Korea Republic of

This research aims to identify factors that affect the technological transition of firms toward industry 4.0 technologies (I4Ts) focusing on firm capabilities and policy impact using relatedness and complexity measures. For the analysis, a unique dataset of Korean manufacturing firms’ patent and their financial and market information was used. Following the Principle of Relatedness, which is a recently shaped empirical principle in the field of economic complexity, economic geography, and regional studies, we build a technology space and then trace each firm’s footprint on the space. Using the technology space of firms, we can identify firms that successfully develop a new industry 4.0 technology and examine whether their accumulated capabilities in their previous technology domains positively affect their technological diversification and which factors play a critical role in their transition towards industry 4.0. In addition, by combining data on whether the firms received government support on R&D activities, we further analyzed the role of government policy in supporting firms’ knowledge activity in new industry 4.0 technologies. We found that firms with higher related technologies and more government support are more likely to enter new I4Ts. We expect our research to inform policymakers who aim to diversify firms’ technological capabilities into I4Ts. © 2022, CC BY.

关键词： Industry 4.0

来源：评论

学校读者我要写书评

暂无评论

How do alliance portfolio factors affect a precision medicine firm’s innovation performance?

引用

Journal of Open Innovation: technology, Market, and Complexity 2021年第3期7卷 203页

作者： Chon, Yucheong Shin, Kwangsoo Technology Management Economics and Policy Graduate Program (TEMEP) Seoul National University Seoul 08826 South Korea Department of Biomedical Convergence College of Medicine Chungbuk National University Chungdae-ro 1 Seowon-gu Cheongju 28644 South Korea

Precision medicine is an approach to disease treatment and prevention that seeks to maximize effectiveness by taking into account individual variability in genes, environment, and lifestyle. The medical paradigm has been changed with the emergence of precision medicine and many companies with business related to precision medicine should cooperate with other companies. The purpose of this study is to analyze the alliance portfolio factors that affect firms’ innovation performance. This study examined whether the diversity factors of the alliance portfolio and alliance management capability influenced its innovation performance. Additionally, we investigated the moderate effects of participation of research organizations in the alliance portfolio. As a result, there was an inverted U-shaped relationship between the industry diversity of the portfolio and innovation performance;therefore, the participation of research organizations in the alliance portfolio showed a positive effect. Additionally, the value governance diversity changed to have a positive effect by interacting with research organizations. This study provides information on the alliance portfolio factors that affect the innovation performance of precision medicine companies. © 2021 by the authors. Licensee MDPI, Basel, Switzerland.

关键词： Alliance diversity Alliance management capability Alliance portfolio Innovation performance Research organiza-tion

来源：评论

学校读者我要写书评

暂无评论

Network externalities in cybersecurity information sharing ecosystems 1

引用

15th International Conference on the economics of Grids, Clouds, Systems, and Services, GECON 2018

作者： Rashid, Zahid Noor, Umara Altmann, Jörn Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul Korea Republic of School of Electrical Engineering and Computer Sciences National University of Sciences and Technology Islamabad Pakistan

ISBN: (数字)9783030133429

ISBN: (纸本)9783030133412

The utilization of cybersecurity information for improving security posture of an organization resulted in the evolution of cybersecurity information sharing ecosystems. In this study, we consider three stakeholders i.e. cybersecurity solution providers, information providers, and end users, who have different values. Their values depend on interrelationship among them and are also based on several value parameters. We identified six value parameters and analyzed their impacts on the values of stakeholders. A simulation model has been developed using system dynamics to analyze the impact of value parameters on the values of stakeholders. The results show that end users are the main source of value in cybersecurity information sharing ecosystems, implying an effect of demand side economies of scale. The cybersecurity solution and information providers are majorly benefiting from a growing number of end users. The value of end users is mainly affected by quality of services, quality of information and the size of trusted communities. © 2019, Springer Nature Switzerland AG.

关键词： Ecosystems

来源：评论

学校读者我要写书评

暂无评论

Correction to: Revitalizing the Concept of Public Procurement for Innovation (PPI) from a Systemic Perspective: Objectives, policy Types, and Impact Mechanisms

引用

Systemic Practice and Action Research 2019年第2期33卷 213-214页

作者： Kiyoon Shin Yeongjun Yeo Jeong-Dong Lee Technology Management Economics and Policy Program Seoul National University Seoul Republic of Korea

The presentation of figures in the manuscript in the online version has some errors. Figures were mixed-up.

关键词：

来源：评论

学校读者我要写书评

暂无评论

How to improve performance and diversity of government-funded research institute ecosystem? Focus on result sharing and feedback policy

引用

Journal of Open Innovation: technology, Market, and Complexity 2019年第3期5卷 66页

作者： Cha, Namjun Hwang, Junseok Kim, Eungdo Technology Management Economics and Policy Program College of Engineering Seoul National University Seoul 08826 South Korea Department of Biomedical Convergence College of Medicine Chungbuk National University Cheongju 28644 South Korea

Despite its importance to the performance outcome of an organization, there are very few studies on how feedback mechanism impacts ecosystems of government-funded research institutes (GIs). This study focuses on the effect of the feedback mechanism on the average performance and diversity of a GI ecosystem. Feedback mechanisms consisted of feedback strategy and degree of result sharing. An agent-based model that embeds a genetic algorithm to replicate a real GI ecosystem was used. It was found that relational patterns between average performance and degree of result sharing varied by type of feedback policy. In contrast, convergence time, which refers to the average period of settling the stable state in the perspective of ecosystem diversity, depends on the ratio of result openness rather than the type of feedback policy. This study suggests two plans to improve the GI assessment system by changing the degree of result sharing and feedback type. © 2019 by the authors.

关键词： Agent based model Feedback Government-funded research and development institute Governmental institute Incentive Organizational assessment

来源：评论

学校读者我要写书评

暂无评论

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案：

请选择收藏分类：

通借通还

建议与咨询 留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

时间限定

文献类型

馆藏选择

核心期刊

语言

文献类型

帮助

文字说明：

检索规则说明：

检索范例：

分类表

所选分类

限定检索结果

文献类型

馆藏范围

日期分布

学科分类号

主题

机构

作者

语言

请选择保存的检索档案： 新增检索档案 确定 取消

请选择收藏分类： 新增自定义分类 确定 取消

通借通还

建议与咨询留下您的常用邮箱和电话号码，以便我们向您反馈解决方案和替代方法

请选择保存的检索档案：

请选择收藏分类：