• Title/Summary/Keyword: Data-driven innovation

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Factors Affecting HR Analytics Adoption: A Systematic Review Using Literature Weighted Scoring Approach

  • Suchittra Pongpisutsopa;Sotarat Thammaboosadee;Rojjalak Chuckpaiwong
    • Asia pacific journal of information systems
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    • v.30 no.4
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    • pp.847-878
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    • 2020
  • In the era of disruptive change, a data-driven approach is vital to Human Resource Management (HRM) of any leading organization, for it is used to gain a competitive advantage. HR analytics (HRA) has emerged as innovative technologies since advanced analytics, i.e., predictive or prescriptive analytics, were widely used in the High Performing Organizations (HPOs). Therefore, many organizations elevate themselves to become HPOs through Data Science on the "people side." This paper proposes a systematic literature review using the Literature Weighted Scoring (LWS) to develop a conceptual framework based on three adoption theories, which are the Technology-Organization-Environment (TOE), Diffusion of Innovation (DOI), and Unified Theory of Acceptance and Use of Technology (UTAUT). The results show that a total of 13 theory-derived factors are determined as influential factors affecting HRA adoption, and the top three factors are "Quantitative Self-Efficacy," "Top Management Support," and "Data Availability." The conceptual framework with hypotheses is proposed to provide a foundation for further studies on organizational HRA adoption.

Innovation and craft in a climate of technological change and diffusion

  • Hann, Michael A.
    • The Research Journal of the Costume Culture
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    • v.25 no.5
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    • pp.708-717
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    • 2017
  • Industrial innovation in Britain, during the eighteenth and nineteenth centuries, stimulated the introduction of the factory system and the migration of people from rural agricultural communities to urban industrial societies. The factory system brought elevated levels of economic growth to the purveyors of capitalism, but forced people to migrate into cities where working conditions in factories were, in general, harsh and brutal, and living conditions were cramped, overcrowded and unsanitary. Industrial developments, known collectively as the 'Industrial Revolution', were driven initially by the harnessing of water and steam power, and the widespread construction of rail, shipping and road networks. Parallel with these changes, came the development of purchasing 'middle class', consumers. Various technological ripples (or waves of innovative activity) continued (worldwide) up to the early-twenty-first century. Of recent note are innovations in digital technology, with associated developments, for example, in artificial intelligence, robotics, 3-D printing, materials technology, computing, energy storage, nano-technology, data storage, biotechnology, 'smart textiles' and the introduction of what has become known as 'e-commerce'. This paper identifies the more important early technological innovations, their influence on textile manufacture, distribution and consumption, and the changed role of the designer and craftsperson over the course of these technological ripples. The implications of non-ethical production, globalisation and so-called 'fast fashion' and non-sustainability of manufacture are examined, and the potential benefits and opportunities offered by new and developing forms of social media are considered. The message is that hand-crafted products are ethical, sustainable and durable.

Case Study: PBL-Driven Healthcare Data Science Specialization and Learning Performance (사례연구: PBL기반 보건의료 데이터 사이언스 특성화교육과 학습성과)

  • Hwa Gyoo Park;Jong Ho Kim
    • Journal of Information Technology Services
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    • v.22 no.1
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    • pp.1-14
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    • 2023
  • This paper aims to share the course, performance and implications of Project-Based Learning (PBL) education in healthcare data science (HDS). The HDS team of the business group of Soonchunhyang University, which was selected for the health care field of 'University Innovation Project', considered that the health care IT-based education of the current university differs greatly from the rapidly changing health care 3.0 environment of the fourth industry, and emphasized the PBL practice-oriented specialization program as a learning model. The PBL focused on self-directed learning experiences, real analysis problems, and team-oriented classes. In other words, it was implemented with three specialized strategies: 'Field Inside Education', 'Fusion-type Track Education', and 'Training to strengthen resilience and change response'. This collaborative, practical learning experience, etc. resulted in significant results. The results were recognized as being rated A by the Korea Research Foundation and the comprehensive evaluation, and the results were significantly elevated through the analysis of the student survey and the results index.

Innovation Patterns of Machine Learning and a Birth of Niche: Focusing on Startup Cases in the Republic of Korea (머신러닝 혁신 특성과 니치의 탄생: 한국 스타트업 사례를 중심으로)

  • Kang, Songhee;Jin, Sungmin;Pack, Pill Ho
    • The Journal of Society for e-Business Studies
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    • v.26 no.3
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    • pp.1-20
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    • 2021
  • As the Great Reset is discussed at the World Economic Forum due to the COVID-19 pandemic, artificial intelligence, the driving force of the 4th industrial revolution, is also in the spotlight. However, corporate research in the field of artificial intelligence is still scarce. Since 2000, related research has focused on how to create value by applying artificial intelligence to existing companies, and research on how startups seize opportunities and enter among existing businesses to create new value can hardly be found. Therefore, this study analyzed the cases of startups using the comprehensive framework of the multi-level perspective with the research question of how artificial intelligence based startups, a sub-industry of software, have different innovation patterns from the existing software industry. The target firms are gazelle firms that have been certified as venture firms in South Korea, as start-ups within 7 years of age, specializing in machine learning modeling purposively sampled in the medical, finance, marketing/advertising, e-commerce, and manufacturing fields. As a result of the analysis, existing software companies have achieved process innovation from an enterprise-wide integration perspective, in contrast machine learning technology based startups identified unit processes that were difficult to automate or create value by dismantling existing processes, and automate and optimize those processes based on data. The contribution of this study is to analyse the birth of artificial intelligence-based startups and their innovation patterns while validating the framework of an integrated multi-level perspective. In addition, since innovation is driven based on data, the ability to respond to data-related regulations is emphasized even for start-ups, and the government needs to eliminate the uncertainty in related systems to create a predictable and flexible business environment.

Identifying Stakeholder Perspectives on Data Industry Regulation in South Korea

  • Lee, Youhyun;Jung, Il-Young
    • Journal of Information Science Theory and Practice
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    • v.9 no.3
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    • pp.14-30
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    • 2021
  • Data innovation is at the core of the Fourth Industrial Revolution. While the catastrophic COVID-19 pandemic has accelerated the societal shift toward a data-driven society, the direction of overall data regulation remains unclear and data policy experts have yet to reach a consensus. This study identifies and examines the ideal regulator models of data-policy experts and suggests an appropriate method for developing policy in the data economy. To identify different typologies of data regulation, this study used Q methodology with 42 data policy experts, including public officers, researchers, entrepreneurs, and professors, and additional focus group interviews (FGIs) with six data policy experts. Using a Q survey, this study discerns four types of data policy regulators: proactive activists, neutral conservatives, pro-protection idealists, and pro-protection pragmatists. Based on the results of the analysis and FGIs, this study suggests three practical policy implications for framing a nation's data policy. It also discusses possibilities for exploring diverse methods of data industry regulation, underscoring the value of identifying regulatory issues in the data industry from a social science perspective.

A Study on the Effect of Startup's Innovation Orientation on Growth Aspiration (창업기업의 혁신지향성이 성장열망에 미치는 영향에 관한 연구)

  • Oh, Hyemi;Lee, Chaewon;Kim, Jinsoo
    • Asia-Pacific Journal of Business Venturing and Entrepreneurship
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    • v.16 no.5
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    • pp.1-14
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    • 2021
  • Innovation and Scale-up of Start-up companies are becoming important national tasks. In the past, it was spread the start-up policy paradigm such as 'Start-up America', 'Start-up Chile', 'Start-up Britain' to overcome the recession globally. However as the economic recovery has become more visible recently in advanced economies, it is shifting from a start-up support policy to a scale-up oriented policy paradigm such as 'Scale-up America', Scale-up UK', 'Scale-up Denmark'. It is necessary to enter the scale-up phase beyond the start-up phase to increase the number of high-quality jobs and to continue economic growth. Therefore, it is necessary to grow the start-up into a strong medium-sized company and to lay the foundation for survival. Therefore, the purpose of this study is to consider the antecedent factors that influence the scale-up aspiration for the start-up firm to grow into a scale-up company, and empirically identifies the differences between the stages of economic development and entrepreneurs in the country. In order to accomplish the purpose, this study predicted scale-up by aspiration which is a predictor of scale-up behavior because it is difficult to achieve visible growth in a short period of time due to the characteristics of start-up companies. In order to empirically explore these relationships, the data were collected from nascent entrepreneurs who have less than 3.5 years of the Adult Population Survey(APS) among the subjects surveyed by the Global Entrepreneurship Monitor(GEM) and the national economic development stage are divided into Innovation-driven, Efficiency-driven, Factor-driven type economies. For the test hypotheses, this study adopted the multi-level model analysis for comparison between national economic development stages and using the R 3.5.0 program. The results of this study are as follows. There is difference between the national economic development and the entrepreneur in the relationship between innovation orientation of entrepreneurs and scale-up aspirations. As the economy of the country develops, the innovation activity of the entrepreneur becomes more active. Since start-ups are heavily influenced by entrepreneurs, there is a difference in the degree of aspiration depending on how innovative an entrepreneur is in the same environment. In terms of the relationship between innovation orientation and scale-up aspiration, the fear of failure was found to differ between national economic development and entrepreneurs. The fear of failure differ from country to country, and this is one of the important factors affecting entrepreneurial activities. It is expected that the factors influencing the growth of the start-up companies which are identified through the results of these studies, will be used to create a suitable scale-up ecosystem according to the national economic development stage.

The Study on the Analysis of Efficiency of Governmental R&D Programs Regarding to the S&T Outcomes (과학기술적 성과 관점에서 정부 R&D사업 효율성 분석에 관한 연구)

  • Park, Seok-Jong;Kim, Kyung-Hwa;Jeong, Sang-Ki
    • Journal of Korea Technology Innovation Society
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    • v.14 no.2
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    • pp.205-222
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    • 2011
  • The Korean government continuously increases the R&D investment in order to pursue an economic growth through technological innovation. Hence, the intensity of governmental R&D has increased rapidly. However, the whole amount of the R&D investment is still small compared to developed countries. And the type of R&D policies is more and more changing from the catch-up model to the technology-driven model. Therefore, there is a growing interest in the efficiency of public R&D investment. Hence, many studies on the efficiency of R&D investment have been researched. This study estimated the efficiency of governmental R&D programs considering the technological outcomes, e.g. theses, patents and so on, using DEA(Data Envelopment Analysis) with data of S&T investment and outcomes from NTIS(National S&D Information Service). In addition, we used the Mann-Whitney Test to investigate the characteristics of governmental R&D investment.

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The Arrival of the Industry 4.0 and the Importance of Corporate Big Data Utilization

  • AN, Haeri
    • East Asian Journal of Business Economics (EAJBE)
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    • v.10 no.2
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    • pp.105-113
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    • 2022
  • Purpose - An increase in automation has been as a result of digital technologies. The data will be instrumental in the determination of the services that are more necessary so that more resources can be allocated for them. The purpose of the current research is to investigate how big data utilization will help increase the profitability in the industry 4.0 era. Research design, Data, and methodology - The present research has conducted the comprehensive literature content analysis. Quantitative approaches allow respondents to decide, but qualitative methods allow them to offer more information. In the next step, respondents are given data collection equipment, and information is collected. Result - The According to qualitative literature analysis, there are five ways in which big data utilization will help increase the profitability in the industry 4.0 era. The five solutions are (1) Better Customer Insight, (2) Increased Market Intelligence, (3) Smarter Recommendations and Audience Targeting, (4) Data-driven innovation, (5) Improved Business Operations. Conclusion - Modern companies have been seeking a competitive advantage so that they can have the edge over other companies in the same industries providing the same services and products. Big data is that technology that businesses have always wanted for an extended period of time to revolutionize their operations, making their businesses more profitable.

A Study on Government Service Innovation with Intelligent(AI): Based on e-Government Website Assessment Data (전자정부 웹사이트 평가 결과 데이터 기반 지능형(AI) 정부 웹서비스 관리 방안 연구)

  • Lee, Eun Suk;Cha, Kyung Jin
    • Journal of Information Technology Services
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    • v.20 no.2
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    • pp.1-11
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    • 2021
  • As a key of access to public participation and information, e-government is taking the active role of public service by relevant laws and policy measures for universal use of e-government websites. To improve the accessibility of web contents, the level of deriving the results for each detailed evaluation item according to the Korean web contents accessibility guideline is carried out, which is an important factor according to the detailed evaluation items for each website property and requires data-based management. In this paper, detailed indicators are analyzed based on the quality control level diagnosis results of existing domestic e-government websites, and the results are classified according to high and low to propose new improvement directions and induce detailed improvement. Depending on the necessity of management according to the detailed indicators for each website attribute, not only results but also level diagnosis to strengthen web service quality suggests directions for future improvement through accurate detailed analysis and research for policy feedback. This study ultimately makes it possible to expect government system management based on predicted data through deduction history management based on evaluation score data on public websites. And it provides several theoretical and practical implications through correlation and synergy. The characteristics of each score for the quality management of public sector websites were identified, and the accuracy of evaluation, the possibility of sophisticated analysis, such as analysis of characteristics of each institution, were expanded. With creating an environment for improving the quality of public websites and it is expected that the possibility of evaluation accuracy and elaborate analysis can be expanded in the e-government performance and the post-introduction stage of government website service.

Climate Change Adaptation Policy and Expansion of Irrigated Agriculture in Georgia, U.S.

  • Park, ChangKeun
    • Asian Journal of Innovation and Policy
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    • v.10 no.1
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    • pp.68-89
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    • 2021
  • The expansion of irrigated agricultural production can be appropriate for the southeast region in the U.S. as a climate change adaptation strategy. This study investigated the effect of supplemental development of irrigated agriculture on the regional economy by applying the supply side Georgia multiregional input-output (MRIO) model. For the analysis, 100% conversion of non-irrigated cultivable acreage into irrigated acreage for cotton, peanuts, corn, and soybeans in 42 counties of southwest Georgia is assumed. With this assumption, the difference in total net returns of production between the non-irrigation and irrigation method is calculated as input data of the Georgia MRIO model. Based on the information of a 95% confidence interval for each crop's average price, the lower and upper bounds of estimated results are also presented. The total impact of cotton production was $60 million with the range of $35 million to $85 million: The total impact of peanuts, soybeans, corn was $10.2 million (the range of $3.28 million to $23.7 million), $6.6 million (the range of $3.1 million to $10.2 million), $1.2 million (the range of -$6 million to $8.5 million), respectively.