Convergence Innovation Research Articles

AI 시대 땅과 공간의 풍수 환경에 관한 연구 - 공주대학교 신관 캠퍼스를 중심으로

The world is changing rapidly. Entering the era of the Fourth Industrial Revolution, China is rapidly evolving into a society of super-intelligence, super-convergence, and hyper-connection. Digital innovation technologies that drive changes in the new era, from big data and blockchain to the Internet of Things and AI, are already deeply embedded in the center of human life. This trend is expected to accelerate throughout society. Feng Shui has long been widely used in various fields to select important locations such as the capital of the country, the residential areas of individuals, and the graves of their ancestors. However, entering the digital age, classical knowledge of Feng S hui faces an inevitable historical turning point through convergence with AI. This represents a great innovation in convergence as well as a structuralist approach to longstanding Feng Shui thinking. Therefore, it is more urgent than ever to think about “new concept Feng Shui marketing,” which can open a new horizon for it by developing big data-based “customized Feng Shui content” that combines it and AI technology and provides related information in real time. To this end, it is necessary to build high-quality data for AI to learn the logic and thinking systems of Feng Shui. In this high school, we analyzed the location environment of the new campus of Gongju National University from a Feng Shui perspective and focused on quantifying the data values derived from it. This was to reduce the ambiguity of evaluation criteria, which is said to be a chronic problem of Feng Shui; and to input clearer and quantified prompts into AI. It is hoped that such research will provide an opportunity to enhance the status and existence value of Feng Shui as a traditional culture and ideology of the Korean people.

Predicting green technology innovation in the construction field from a technology convergence perspective: A two-stage predictive approach based on interpretable machine learning

The construction industry, as a major global energy consumer and carbon emitter, plays a crucial role in achieving global sustainability. A key strategy for the green transformation of this industry—without compromising development—involves fostering green technology innovation. Nevertheless, existing studies exhibit a notable gap in identifying and evaluating potential green technology innovation opportunities within the construction field, leading to a scarcity of decision-making information for governments and innovation entities during the research and development stage. Recognizing this, our study proposes a two-stage technology opportunity prediction approach based on interpretable machine learning from the perspective of technology convergence. Diverging from previous methods, it not only predicts the probability of technology opportunity occurrence but also forecasts the technical impact of convergence opportunities. By analysing 600,442 patent documents in the green and construction fields, we identify 305 high-potential technology convergence opportunities. Our results reveal that technologies such as carbon capture and storage, pollution alarms, solar energy, forestry techniques, wind energy, energy-saving methods, and waste materials for water treatment have significant potential for convergence with construction technologies. Additionally, we analyse the influencing factors behind these convergence innovations, finding that technical similarity and proximity play crucial roles. These findings provide robust decision support for governments and industry stakeholders in formulating scientifically grounded green technology innovation strategies, thereby accelerating the green transformation of the construction industry and contributing to the goal of sustainable development.

Research on the Sustainable Evolution Mechanism of Dual-Dimensional Convergence Innovation in Digital Products

The complex characteristics of cross-disciplinarity, dynamic expansion, ambiguity, diversity, and the rapid changes in demand significantly amplify the uncertainties in digital product innovation. The existing innovation theories, such as “stage-gate”, open innovation, agile development, and data-driven decision making, are insufficient for fully and effectively addressing these uncertainties. Based on a case study of a fintech app, we reveal that digital product innovation is similar to biological evolution, exhibiting dual life-like features of “inheritance” and “mutation” within “dual-dimensional convergence”. However, unlike natural evolution, the evolutionary process of digital product innovation can augment its use of the digital ecosystem and capabilities, establish a data-driven rapid proactive selection mechanism for the main three stages, and quickly enhance product competitiveness. The complexity of knowledge in the innovation process can be partially solved through the use of a micro-knowledge integration learning mechanism formed by the interactions of social and cognitive translation. This study also discovers that market competition and policy regulation are two unique innovation-driven characteristics in digital product innovation. This mechanism can achieve the earlier clarification of product evolution’s direction, reduce the three major uncertainties of innovation, and improve efficiency in the utilization of innovation resources to achieve sustainable development.

Uncovering the impact of technology convergence on innovation quality: From the perspective of ego‐network dynamics pathway

AbstractThis paper examines the mediating effect of R&D alliance network dynamics on the relationship between technology convergence and firm innovation quality, it further investigates the moderating effect of degree assortativity in the inventor network. An empirical analysis is conducted based on a panel negative binomial regression model with data of Chinese high‐tech firms listed on the Shanghai and Shenzhen Stock from 2000 to 2018. The results show that novel technology convergence not only contributes to innovation quality directly but also indirectly through ego‐network expansion. The relationship between reinforced technology convergence and innovation quality is inverted U‐shaped, partially mediated by ego‐network stability. In addition, degree assortativity suppresses the effects of novel technology convergence on ego‐network expansion and innovation quality and steepens the inverted U‐shaped relationships of reinforced technology convergence with ego‐network stability and innovation quality. This paper contributes to the relevant literature by revealing the links between technology convergence, ego‐network dynamics, and innovation quality, and emphasizing the importance of inventor collaboration ties formation mechanism in knowledge searching and convergent innovation. Furthermore, the conclusion provides managerial suggestions for high‐tech firms to coordinate internal and external resources to improve technical impacts.

Convergence innovation for sustainable development: Unraveling post‐COVID dynamics for a resilient future

AbstractThis paper explores the potential of Convergence Innovation (CI) as an effective catalyst for dealing with the COVID‐19 pandemic and devising a trajectory toward a sustainable post‐crisis future. It offers novel perspectives on sustainable innovation approaches that can enhance organizational performance and extend beyond it. The paper makes significant contributions to both the theoretical and practical aspects of innovation. It illustrates the impact of market forces in the context of the Fourth Industrial Revolution (4IR) and Digital Technologies (DT), highlighting the significance of sustainable innovation for organizational prosperity and individual welfare. Convergence Innovation is explained as a self‐regulating ecosystem that promotes and goes beyond value creation. Different technologies in the ecosystem enhance CI's sensing capabilities for fluctuations in market forces and facilitate the transmission of data for decision‐making. The study recommends splitting off the S‐curve of innovation and the life cycle of competitive intelligence, as the S‐curve of CI tends to be shorter in the digital age. This paper provides managers with a new framework for thinking about innovation and its role in achieving sustainable business success. By embracing CI, managers can create more agile and adaptable organizations that are better positioned to navigate the complex and rapidly changing world of the digital age.

Topic Mining and Future Trend Exploration in Digital Economy Research

This work proposes a new literature topic clustering analysis framework, based on which the topics of digital-economy-related studies are condensed. First, we calculated the word vector of keywords using the FastText model, and then the keywords were merged according to semantic similarity. A hierarchical clustering method based on the Jaccard coefficient was employed to cluster the domain documents. Finally, the information gain method was applied to estimate the high-gain feature words for each category of topics. Based on the above framework, 23 categories of research topics were formed. We divided these topics into layers of digital technology, convergence innovation and digital governance, and we constructed a three-level digital economy research framework. Thereafter, the current hot spots and frontier trends were derived based on the number and growth rate of the literature. Our study revealed that the research on digital technology, which is the basic layer of the digital economy, has waned. The field related to the integration and innovation of digital technology and the real economy was the current research focus, among which the results with respect to “New Business Forms in the Digital Age”, “Circular Economy” and “Gig Economy” were abundant. The problems of the unbalanced development of the digital economy and digital monopoly have strengthened research on digital governance. Furthermore, research on “Regional Digital Economy”, “Chinese Digital Economy” and “Data Management” is in its initial stage and is a potential area of future research.

Predicting and analyzing technology convergence for exploring technological opportunities in the smart health industry

Technology convergence (TC) represents a prevailing innovation pattern in various industries, as it enables the integration of two or more existing technologies to create new hybrid technologies or even a new technological domain, transforming the way firms compete with each other. The advent of smart health can be attributed to the convergence of various technologies, including wireless communication, embedded systems, artificial intelligence (AI), medical technologies, and information security. It is essential for smart health firms to systematically comprehend TC patterns and anticipate emerging convergent technologies at an early stage to leverage potential technological opportunities. This paper proposes a machine learning methodology that integrates network analysis to predict and analyze changing TC patterns from patent data related to smart health. A machine learning-based link prediction method is developed to forecast convergent technologies from a comprehensive set of link prediction measures. Network centrality analysis is then used to understand and evaluate the convergent patterns in the predicted technological knowledge interaction network and identify critical convergent technologies that may play significant roles in the future. The research not only demonstrates that convergent innovation is a continually growing trend in the smart health industry but also identifies several important emerging convergent patterns.

Institutionalisation of convergent medical innovation: an empirical study of the MRI-guided linear accelerator in the Netherlands and the United States

ABSTRACT Although convergence is a major trend in the development of medical innovations, the implications of the institutionalisation of convergent innovation are understudied. This paper explores how the institutionalisation of convergent innovation affects the organisation of health care, by using operational domains and categories of the Non-adoption, Abandonment, Scale-up, Spread and Sustainability (NASSS) and the Institutional Readiness (IR) approach respectively. We use an illustrative comparative case study on the institutionalisation of MRI-guided linear accelerator (MR-Linac) technology in the Netherlands and the United States. Empirically, we conducted 66 interviews with different professionals in the health care system around MR-Linac. The findings show that institutionalisation of convergent innovation affects the organisation of health care by: changing the traditional organisation of solving a medical problem, thereby transforming and reorganising work in the health care environment, providing opportunities for individual user development, collective action and cross-sectoral developments, and requiring the additional work of evaluating convergent innovation, including administrative tasks, innovation and research activities within and across institutions. The insights offered are also relevant for understanding convergence in the medical field, and for rethinking medical innovation in general.

Testing for Convergence Innovation and Club Clustering in Selected Economies 1995-2017

Innovation convergence is a deterministic process resulting from the change in micro and macro innovation determinants. It is characterized by firms' search for innovative opportunities in other economic sectors and in their development from mining through heavy industry to material processing sector, discovering new technologies that connect individual products to a more integrated global system, diversifying, ensuring technical scope growth, and start-ups contributing to new managerial leadership. The aim of this study is to contribute to our knowledge of convergence innovation by providing empirical evidence on it. To this purpose, we use a nonlinear time-varying factor model to test for convergence innovation and countries' club clustering. For the sample of 29 countries from 1995 to 2017, we identify two significant convergence clubs and one divergent group (Cyprus, Czech Republic, and The Netherlands). The empirical evidence indicates that innovation singularity could appear as a significant barrier and limiting factors for firms' and countries' growth in the future. Design and new product development trends in these countries follow a different decoupling path from the rest of the sample. Policymakers and practitioners should carefully evaluate innovation determinants and constraints (decoupling drivers) in setting up innovation policies on a micro and macro level.

The Role of Environmental Practices and Innovation in Total Factor Productivity Convergence – Evidence from Small and Medium-sized Manufacturing Enterprises in Vietnam

Cette recherche examine le lien entre la conformité environnementale, l’innovation et la convergence de la productivité totale des facteurs. Nous utilisons deux mesures de pratiques environnementales : la norme de certification environnementale et le traitment environnemental. Quant à l’innovation, il s’agit d’une variable qualitative ayant trois modalités croissantes : aucune innovation, innovation de produit ou de procédé et deux types d’innovation. En utilisant une base de données des petites et moyennes entreprises manufacturières vietnamiennes entre 2007 et 2015, les pratiques environnementales ne sont pas corrélées avec la productivité totale des facteurs. En revanche, il existe une forte corrélation entre l’innovation et le traitement environnemental. Les facteurs qui contribuent au taux de croissance de la productivité des entreprises, et par conséquent à la vitesse de convergence, sont l’innovation, la taille de l’entreprise et la forme juridique.

Industry convergence and value innovation: a bibliometric analysis and systematic review

PurposeThe purpose of this paper is twofold: first, to present a bibliometric analysis and systematic literature review of industry convergence and value innovation to understand the current research status; second, to provide a coherent theoretical research framework for future research.Design/methodology/approachThis study adopts a two-step analysis approach by combining bibliometric analysis and systematic literature review to explore the research topic of industry convergence and value innovation. Besides, two bibliometric tools, HistCite and VOSviewer, were applied to this study.FindingsThis study found that Stefanie Bröring and Fredrik Hacklin are the top two most influential authors among all authors in the sample publications. Technological Forecasting and Social Change is one of the top-ranking journal that often publishes this topic of articles. Germany and the University of Munster are the most influential country and institutions, respectively. Besides, five core research themes were identified based on keywords co-occurrence map, theoretical lenses, factors promoting industry convergence, indicators of industry convergence, the impact of industry convergence and emerging research directions. Based on the above analysis, this paper constructed a theoretical research framework of industry convergence and value innovation.Research limitations/implicationsThis paper only draw data from one database – Web of Science – which cannot provide broad coverage of the research topic. Besides, the bibliometric method of this paper is based on high local citation score and high-frequency words, articles in the skirting subjects’ area may not be analyzed.Practical implicationsWith the rapid development of technology, such as nanotechnology, radio - frequency identification (RFID), etc., the iterative upgrading of products also comes. As a result, the boundary between industries is gradually blurred, and the phenomenon of industry convergence appears. Therefore, managerial decision-makers are facing challenges of how to respond to the convergence phenomena. From the firm level, firms are facing the problem of value innovation of the existing product, new product development and core competence improvement. Industries are facing the problem of transformation and upgrading. This paper provides certain theoretical insights for both firms and industries to guide the practice accordingly.Originality/valueThis paper is the first to use a bibliometric method to examine the topic of industry convergence and value innovation. In addition, this paper presents an in-depth analysis of this topic and provides a comprehensive theoretical research framework for future study.

A Review on the Cause, Advantages, Challenges, and Future of Media Convergence

Individuals’ lifestyles have become increasingly dependent on media convergence. Human careers have been made more manageable, and their access to media has increased because of technological advancements in television, the Internet, and mobile communication. However, the idea of whether or not media convergence offers benefits and problems to the industry around the world must be questioned. Radio and entertainment companies have difficulty integrating media because of various issues, including dwindling broadcaster personalities, shifting media discourses, and rapid advances in AI. However, media convergence must contend with the economic advantages and changes brought by an expanding audience; the present media technology advancements; and the public’s increased literacy, impact, and direct communication. Convergence innovation and development are prevented by a unique broadcasting and hosting method, a new media development process, and an expansion of media cultural network capacity. Finally, the media convergence industry’s future development prospects in the age of fusion media are forecasted. Keywords: advantage ; cause; challenge future trend; media convergence

Formation mechanism for integrated innovation network among strategic emerging industries: Analytical and simulation approaches

It is necessary to study the evolution process and the periodicity of the integrated innovation network among strategic emerging industries (SEIs) to improve the network operation efficiency and the overall innovation performance of the industry. Therefore, firstly, we analyze the characteristics of the integrated innovation network among SEIs and the B-Z (Belousov–Zhabotinsky) reaction model. Then, the applicability of the B-Z reaction model to the innovation network is discussed. Secondly, we propose a three-dimensional dynamic evolutionary model of integrated innovation potential, network structure embeddedness and integrated innovation performance and present an empirical simulation analysis. Finally, the integration of Huawei and new-energy vehicle enterprises is used as a case study for verification and analysis. According to the results, firstly, the higher the level of external support, the faster the improvement of integrated innovation potential, which shows a distinct trend of rapid synergistic growth with integrated innovation performance. However, improving the network structure embeddedness through external support is more difficult. Secondly, in the time dimension, the development trend of convergence innovation potential and system evolution is an inverted U-shaped curve. Thus, the innovation subject should take appropriate measures according to the industrial growth stage. Thirdly, different SEIs have markedly heterogeneous evolution paths of system advancement, so each subject should make reasonable decisions according to its own integrated innovation potential level and external support threshold. The research results are verified by analyzing Huawei's integration with the new-energy vehicle industry as a case study, and the results are expected to provide a theoretical basis for enterprise decision making. By referring to the conclusions of this paper, the government can formulate targeted industrial policies based on the status quo of industrial development.

Hotel service convergence innovation

ABSTRACT Industry convergence has taken place in many different fields, making it a hot research topic. There are studies on industry convergence in the manufacturing industry, the food and pharmaceutical industries, and between manufacturing and services industries. The hospitality industry provides lodging and catering services, which provides a great platform to integrate multiple industries in order to enhance customer experience. However, there has been little focus on industry convergence in the hospitality or hotel industries. Therefore, a better understanding of service convergence innovation from both a systematic and a holistic perspective are needed. The result showed that in order to form effective mechanisms for coordination and integration of service, it was necessary to use systematic digital information technology, which could transfer practical experience into a standardized demonstrable learning database system. The implication of this study is that the illustrations on the factors as well as contexts to foster service convergence practices could facilitate managerial endeavors by hospitality business professionals. Appropriate incentive mechanisms which leverage as well as motivate partnership endeavors should be the core aligning individuals and organization goal instead of imposing regulative order.

Multi-indicator supply chain management framework for food convergent innovation in the dairy business

A comprehensive integrated framework of indicators currently used in lean, agile, sustainable and resilient supply chain paradigms is developed under the umbrella of convergent innovation (CI) and applied to the management of the supply chain of a dairy company, including procurement, processing and distribution of their products to customers. CI is a meta-framework that opens new frontiers for commercial innovation, supply chains and market systems by making the convergence of economic, social and environmental outcomes the target of business and actor decisions throughout society to build supply and demand for commercially viable outcomes. This framework provides a company with a multi-indicator supply chain management tool designed to accommodate the supply chain paradigms of being lean, agile, sustainable and resilient, as well as providing milk-based essential nutrition within a process called convergent innovation. The proposed analytical framework can serve as a decision support tool to systematically evaluate and improve the dairy supply chain from plant production to retailers. In jurisdictions without a quota system for milk production at the farm level, the system constructed in this paper could be expanded to handle farm production and shipment to dairy processing plants.

Convergence innovation in the digital age and in the COVID-19 pandemic crisis

Sustainable innovation is imperative for organizational survival and success in the turbulent market environment of the digital age, especially more so in the current COVID-19 pandemic crisis. This paper presents convergence innovation (CI), powered by the exponential fusion effect of the various objects, technologies, ideas, and strategies, as a new sustainable core competence of organizations. We present the concept of CI including its autonomous ecosystem enabled by advanced technologies, unique life cycle features, relationships with other innovation approaches, and its purpose of value creation for the stakeholders and beyond (for the greater good). The paper also explores how CI can be a catalyst for managing the current COVID-19 pandemic and charting the path to post crisis. The study makes contributions to both innovation literature and to practicing managers with new insights on sustainable innovation strategies for organizational performance and beyond.

Convergence strategy and innovation capability of the classic art industry

Arts management is the field related to business operations of arts organizations, specifically production, fundraising, policy and administration, public relations, marketing, etc. The main characteristic of the field of art is that it requires talented people as the main input for value creation, and this requires effective management of resources and processes. The purpose of this study is to investigate the potential of a convergence strategy for improving the sustainability of the opera industry by focusing on operama, a new genre created through the fusion of opera and drama. Through the convergence of the two different industries, operama has been able to communicate the philosophy and artistic values of classic art to the public more effectively. This study proposes how classic art industries can be positively reinvented by adopting various convergence strategies.

Convergence Innovation: A Case Study of Digital Cable TV in Taiwan

The purpose of this study is to explore the impact of the digital TV industrys innovative business model on customer demand and product service. The research method is based on the case study method in qualitative research. Based on the current state of the industry and market demand, this study uses a three-tier business model to conduct exploratory research from five perspectives: 1) Innovation, 2) Value, 3) Resource, 4) Market, and 5) Profit. The research results show that: 1. In order to pursue sustainable survival, enterprises should adapt to market changes, constantly adjust their operational direction and innovative business models; 2. Through product innovation, service innovation and technological innovation, enterprises can effectively pass on the value proposition to customers and create the profit of the enterprise. In addition, in the research findings, the “innovative value” that this study failed to mention is worthy of continuous research to increase the contribution of research.

Technology convergence capability and firm innovation in the manufacturing sector: an approach based on patent network analysis

As a consequence of the convergence between manufacturing technology and the foundation technologies of Industry 4.0, it is becoming more important for firms to formulate an innovation strategy for their technological capabilities. In this context, the present study measures firm‐level technology convergence (TC) capability using patent network analysis. A firm’s TC capabilities are measured using three centrality indices pertaining to a patent network, which is constructed based on the relationship between patents and their international patent classification. For the empirical analysis, panel regression is conducted to observe the effect of TC capabilities on innovation for the top 30 firms in four manufacturing industries. We find that the TC degree positively influences the firms’ overall innovation, namely their total number of patents, and negatively influences their convergent innovation, calculated as the ratio between the number of TC patents and the total number of patents, while the effect of TC betweenness is the opposite. These findings imply that while concentrating on similar technologies may promote quick technology application, it could hamper the enhancement of a TC’s potential. To promote TC, a firm should thus develop technologies more likely to be involved in TC.

Impact of Construction IT Technology Convergence Innovation on Business Performance

As the era of the fourth Industrial revolution begins, there is high demand for new information technology (IT) innovation to address the challenges of a dramatically changing industrial landscape. The construction industry, which is one the most important traditional industries in Korea, has adopted new IT innovation in their products to meet customer demand, regulation from government, energy efficiency, security, and so on. The aim of our study is to empirically clarify the impact of technology innovation on the business performance for Korean domestic construction conglomerates. The study performs an empirical analysis with time series analysis on business performance from the perspective of client satisfaction with the services the target companies provide and the production process improvement, as well as from a financial perspective. As analysis data, statistical data from the Ministry of Science, ICT, and Future Planning; Brand Stock; Bank of Korea; and each company are utilized, and the target companies for our study are limited to 19 construction companies with an apartment brand. Multiple regression analysis is used as a fundamental analysis methodology of our study. For Time Series Analysis, the Box Jenkins Model, namely, ARIMA is utilized. According to our results, it is found that any improvement of IT convergence innovation competence such as business efficiency IT index, collaboration IT index, and strategy management IT index has a positive impact on the production process, financial performance, and customer satisfaction with the services the companies provide.