Special Issue "Open Innovation and Business Models in Electronics after COVID-19 Pandemic"
Deadline for manuscript submissions: 31 December 2021.
Interests: open innovation; business model; open innovation economy; social open innovation; Schumpeterian dynamics; complexity; game theory; political economics
* Managing Guest Editor
Special Issues and Collections in MDPI journals
Special Issue in Sustainability: Sustainability of Economic Growth: Combining Technology, Market and Society
Special Issue in Sustainability: Sustainability of Economy, Society, and Environment in the 4th Industrial Revolution
Special Issue in Journal of Open Innovation: Technology, Market, and Complexity: The 4th Industrial Revolution from Open Innovation in Manufacturing and Service Industry to Cyber-Physics
Special Issue in Journal of Open Innovation: Technology, Market, and Complexity: Second IT Revolution and Dynamic Open Innovation: From Smart City, Autonomous Car, Intelligent Robot, and Block Chain to Sharing Economy
Special Issue in Electronics: Electronics and Dynamic Open Innovation
Special Issue in International Journal of Environmental Research and Public Health: Environmental Research, Public Health, and Dynamic Open Innovation: From Smart Cities to the Sharing Economy
Special Issue in Journal of Open Innovation: Technology, Market, and Complexity: Ambidextrous Open Innovation: Technology, Market and Complexity
Special Issue in Sustainability: Ambidextrous Open Innovation for Sustainability
Special Issue in Journal of Open Innovation: Technology, Market, and Complexity: Open Innovation and Business Model in the Global Economic Crisis Which is Triggered by the Pandemic of COVID-19
Special Issue in Sustainability: Open Innovation and Business Model for Economy Sustainability after the COVID-19 Pandemic
Special Issue in International Journal of Environmental Research and Public Health: Open Innovation in the Research and Industry about Natural Environment and Public Health after Pandemic of COVID-19
Interests: open innovation; system dynamics; management science; strategic management; digital transformation; decision support systems
Special Issues and Collections in MDPI journals
Interests: technological innovation; social innovation; knowledge management and strategic management that have a good influence on change in the world
Interests: artificial intelligence and big data analyses in open innovation; new generation communication and networking systems
Special Issues and Collections in MDPI journals
In the COVID-19 pandemic, several global offline industries, such as air travel, tourist, hospitality, and entertainment, have been shut down for nearly a year. However, online industries, such as retail, delivery, online and mobile contact, and cloud computing, are showing significant growth with diverse, creative open innovation and new business models in electronics, information and communication technologies, robotics, artificial intelligence, and big data.
Open innovation and new business models in electronics after the COVID-19 pandemic will appear as new growth engines for the recovery of the global economy. Therefore, in order to encourage researchers and business professionals to increase progress in electronics, including artificial intelligence, big data, Internet of things, cloud computing, autonomous cars, and intelligent robots, we would like to set up this Special Issue in order to publish the latest research works on, but not limited to, the following topics:
- New open innovation in electronics after the COVID-19 pandemic;
- New business models in electronics after the COVID-19 pandemic;
- Artificial intelligence open innovation after the COVID-19 pandemic;
- Autonomous car open innovation after the COVID-19 pandemic;
- Big data open innovation after the COVID-19 pandemic;
- New digital open innovation after the COVID-19 pandemic;
- New game open innovation after the COVID-19 pandemic;
- New smart manufacturing systems open innovation after the COVID-19 pandemic;
- New digital open innovation after the COVID-19 pandemic;
- New smart living open innovation after the COVID-19 pandemic;
- New smart city open innovation after the COVID-19 pandemic.
Time schedule for this Special Issue:
- Special Issue Opens: 10 June 2021
- From 10 June 2021, any SOI 2021 authors, in addition to the planned papers, can submit to this Special Issue after full paper submission to the SOI 2021 platform and paying the registration fee until 31 December
- Special Issue Closes: 31 December 2021
All papers should be submitted to this Special Issue by 31 December 2021.
Prof. Dr. JinHyo Joseph Yun
Prof. Dr. Min-Ren Yan
Prof. Dr. Jeonghwan Lee
Prof. Dr. Tae-Eung Sung
Manuscript Submission Information
Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.
Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Electronics is an international peer-reviewed open access semimonthly journal published by MDPI.
Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1800 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.
The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.
Authors: Csaba Mako *, Miklos Illess
Abstract: The fear of job losses due to labor-saving technological change dates back to the nineteenth-century Luddites in Britain and is, therefore, not a new phenomenon. Recently, similar concerns have reawakened due to the rapid expansion of increasingly inexpensive and capable computers (digitization) and the automatization of some of the tasks that were formerly undertaken by workers. According to the empirical findings of European Working Condition Surveys (EWCS, 2005; 2015), every second workplace involves a form of “creative work”, which is less threatened by automation, while every fourth worker carries out “routine” tasks that could be easily replaced by computers. However, important country-group-level differences exist: creative jobs are found at rates above the EU-27 average in Nordic, Continental, and Anglo-Saxon countries, while Mediterranean and Central and Eastern European countries are characterized by the highest proportion of jobs involving routine tasks. Among the post-socialist countries, Hungary lags behind the European average, and job loss trends suggest that concerns about the impacts of automatization on the job market for unskilled workers are valid.
Keywords: automatization; digitization; employment; working conditions; EU
Title: Digital Innovation and Unemployment in An Agent-Based Economy with Dynamic Substitutability Between Labor and Capital
Authors: Filippo Bertania *, Marco Rabertoa, Andrea Tegliob, Silvano Cincottia
Background and Motivation: Since the ﬁrst industrial revolution, the potential consequences deriving from new waves of technological progress have been discussed and conﬂicting opinions have been generated. New technologies have always generated apprehension among the working class, and, even if the debate among economists is still open, most of them agree on distinguishing between negative short-run and positive long-run eﬀects, see Mokyr et al. (2015). Most of the innovations introduced within production systems until the end of the 20th century had the purpose of producing a huge amount of mechanical energy, which allowed the limits imposed by human physical force to be surmounted. Nowadays, according to Brynjolfsson and McAfee (2014), we are experiencing a new technological revolution called “The Second Machine Age”. In this new era, through the adoption of new digital technologies such as AI, we can overcome limits imposed by our mind. The primary objective to be pursued in adopting these new digital instruments is represented by the automation of decision-making processes, and this new kind of automation makes us reﬂect on its potential future consequences on the labor market. In particular, the target of technological unemployment could change from “blue-collar workers” to “white-collar workers”. Recent empirical studies have shown that since the end of the 20th century the labor market has been experiencing a job polarization that is not fully consistent with the “skill-biased technical change” hypothesis, which states that technical change favors skilled over unskilled workers (Autor and Dorn, 2013; Goos and Manning, 2007; Goos et al., 2014). On the contrary, according to this empirical evidence, the recent technological progress has to be seen as routine-biased: the jobs most threatened are not necessarily the lowest skilled ones but are mostly those characterized by a high routine level. In order to forecast potential eﬀects deriving from digital technology innovation, it is important to frame how these technologies aﬀect our production systems. In this respect, we have theorized an alternative production function based on the notion of an organizational unit. This new conceptual production technology is integrated within the well-known large-scale macroeconomic model Eurace (Raberto et al., 2012; Ponta et al., 2018; Teglio et al., 2019). In particular, we build on the latest version of the Eurace model, which encompasses intangible digital technologies, as presented in Bertani et al. (2019, 2020), replacing the Cobb–Douglass technology used to model the manufacturing processes in a traditional mass-production system with a Leontief production function in which input factors are represented by organizational units. Furthermore, in the new framework, technological progress does not aﬀect the productivity level but the nature of technology itself: innovation aﬀects the degree of substitutability between capital labor and changes the elasticity of substitution.
Keywords: intangible assets; digital transformation; technological unemployment; agent-based economics; organizational unit
Title: Can the AI Revolution be Labor-Friendly? Some Micro Evidence from the Supply Side
Authors: Giacomo Damioli *, Vincent van Roy, Daniel Vertesy, Marco Vivarelli
Abstract: Purpose/Research Question: The past two decades have witnessed major developments in artificial intelligence (AI) technologies (WIPO, 2019; Van Roy et al., 2020). As for previous technological revolutions (think, for instance, of the diffusion of ICT in the last few decades of the past century), AI has a remarkable disrupting potential across firms, industries, economies and societies. In this paper, we analyze the impact of AI technologies on employment dynamics at firm level. Key Literature Reviews: In particular, the possible adverse impact of AI diffusion and robotics on employment has generated concerns and vivid discussions in the academic debate and in society as a whole. While most of the (recent) extant literature focuses on the demand side (i.e., the adoption of AI and robots as labor-saving process innovations in downstream industries, e.g., Acemoglu and Restrepo, 2018, 2019 and 2020; Autor et al., 2003; Barbieri et al., 2020; and Graetz and Michaels, 2018), there is a gap in the literature with regard to the supply side, i.e., the possible job-creation effect of AI technologies conceived as product innovations in the upstream sectors. Design/Methodology/Approach: Within this framework, our study aims to assess the micro-level employment impact of AI and robotics, focusing on a worldwide set of 3500 front-runner companies that patented the relevant technologies in 2000 to 2016. Using balance sheet information from Bureau Van Dijk’s ORBIS database combined with the Worldwide Patent Statistical database (PATSTAT) of the European Patent Office, the empirical analysis employs a dynamic panel data model (GMM-SYS) to control for endogeneity and for persistent firm-level differences in employment level. Research Limitations/Implications: The evidence suggests that technological leaders within the emergence of the AI paradigm can realize labor-friendly outcomes; however, heterogeneity is also detected, with large and less-technology-intensive manufacturing companies perhaps needing more time (and a more established technological shift) to couple product innovation with job creation.
Keywords: technological change; artificial intelligence; robotics; employment; GMM-SYS
Title: Evolutionary Game Research on Value Co-Creation Behavior of Digital Patent Platform
Authors: Xiaojing Huang, Lei Ma *, Rao Li, Zheng Liu *
Abstract: Purpose/Research Question: With the development of the sharing economy and the improvement of the network environment, a large number of platform-based companies have emerged in the fields of production, life, and public services, bringing tremendous impact and changes to many traditional industries, and platform business models have gradually become the mainstream development trend. Network information technology represented by cloud computing, big data, and artificial intelligence has greatly promoted the development of the platform, making the platform evolve from a pure product platform/virtual platform to a platform enterprise and then develop and grow into a platform ecosystem. A patent digital platform is a cross-enterprise (or institution) organization composed of government agencies, enterprises and institutions, scientific research institutes, intermediary agencies, and other relevant social groups that use digital technology to jointly create, manage, protect, and serve patents with patent operation enterprises (or institutions) as the core. They are guided by value co-creation, use market mechanisms to gather innovation resources, and form an innovation system that combines government, industry, research, and application. The participants of the patent digital platform include the patent digital platform enterprise (the platform owner), the government (the platform regulator), and the trading party (the platform user). In view of the influence of the decision-making of digital patent platform participants (owners, regulators, and users) on the stability of a sharing economy system, based on the network externality of the platform, the interactive influence of participants' behavior, and the assumption of bounded rationality, an evolutionary game model composed of "owner–regulator–user" is constructed. The evolutionary stability of the equilibrium point and the evolutionary stability strategy of the system are analyzed by using the evolutionary game theory and the Lyapunov discriminant method. Finally, this paper discusses the impact of network externality, participant opportunism cost, and platform supervision on the stability of the dynamic system so as to provide a theoretical reference for participants' behavioral decision-making.
Keywords: digital patent platform; tripartite evolutionary game; network externality; evolutionary stability strategy
Title: Predicting Trends in Digital Business Innovation Development
Authors: Anna Svirina *, Polosukhina Ekaterina, Segeev Nikita
Abstract: Purpose/Research Question: Existing research of digital startups has mainly been focused on the issues of innovation development and market acquisition (Bell et al., 2004; Ribai et al., 2018) as a platform for efficient internationalization. The other research direction in the assessment of startups’ efficient international development lies in the field of evaluating their human workforce, which is being seen as the key resource of emerging digital sphere companies (Alvarez and Busenitz, 2001; Novak and Bojnec, 2005). The abovementioned and other relevant factors have been proven to be an important driver of SME digital development; the evidence behind this has come mainly from the startup companies themselves rather than evaluating an outside estimation of companies’ state of development. In this study, we have acquired original data from the experts of venture capital funds, whose job it is to pre-assess startups prior to investment analytics. Thus, we have acquired a different angle, which has allowed us to see the level of success of digital startups in their internationalization.
Title: Effects of Information and Communication Technology (ICT) Bases on Cross-Border M&A Performance: Evidence from the Acquire and Target States
Authors: Junghyun Kim, Jeonghwan Lee *
Abstract: As cross-border M&As proliferate, the characteristics and purpose of M&As also evolve. Cross-border M&A has been a great means to accomplish economies of scale and scope, prior occupation of the markets, and diversification for corporate portfolios. However, recently concluded M&As differ from the M&As concluded in the past. Firstly, a M&A is executed for long-term perspective. As the rise of soft power hedges social transparency and political uncertainty, it also raises economic optimism for long-term market presence. Secondly, technological M&As, including technological similarity and technological digestibility, affect the assimilation, transformation, and exploitation processes of the absorptive capacity (G.S. Jo et al., 2016). In general, the right technological chemistry between acquire and target states firms would create synergy effects, which are the key to success and lead to innovation. These imply the importance of which soil to plant a tree with. If the soil has maturities of ICT infrastructure bases, it would have wielded strong influences for inducing M&A completion. The effects would be reciprocal, as both acquiring and target firms might be matched and selected to be appropriate for each other. To systematically examine the factors that need to be considered in “cross-border M&A completion under ICT maturities bases”, this framework adopts a data sample representative of the ICT development indices of six regions with more than 180 national and international state firms indicated on the SDC Platinum database list in 2014–2018. The study supports empirical evidence that the cross-border M&A deal completion can benefit from ICT maturities in target states. On the specifics, the findings suggest that the degree of ICT in target states will accelerate M&A completion.
Keywords: ICT M&A; technological M&A; absorptive capacity; soft power; cross-border M&A
Title: COVID-19 Response Success Factors of Quarantine and ICT Utilization Capability
Authors: Ki soon Shin, Eungdo Kim *, Shin Kwang Soo
Abstract: Purpose/Research Question: The World Health Organization (WHO) and the Global Health Security Index (GHS Index) assess and rank the capabilities of each country to respond to an infectious disease crisis. However, in the COVID-19 pandemic, infection rates, mortality rates, and social turmoil have been different from the rankings. What factors were missed by the existing evaluation criteria, and what made the difference in each country? This study compares the health systems and quarantine policies between countries from the perspective of open innovation and attempts to identify more pragmatic evaluation factors revealed in the responses of each country to COVID-19. According to the COVID-19 response policies and the ICT utilization capability, we compare the health damage, economic shock, and the resilience of the people.
Keywords: COVID-19; health security; ICT utilization capability
Title: Deep-Learning-Based Predictive Maintenance and the Applications of Adaptive Bollinger Bands for Anomaly Detection in Manufacturing Data
Authors: Ji-Hye Choi, Min-Seung Kim, Yong-Ju Jang, Chan-Ho Lee, Tae-Eung Sung *
Abstract: Purpose/Research Question: 1. Anomaly detection is an important problem that has been well studied within diverse research areas and application domains. In this paper, an effective anomaly detection method is proposed to quickly detect an anomaly value when real streaming data are entered, without any special pre-processing required. 2. It aims to detect anomaly values in manufacturing data among many fields. Its purpose is to prevent serious failures in advance and to reduce damage by constructing a model that detects anomalies based on time series data measured from various sensors. 4. Stock data are typical examples of time series data that change over time. Bollinger Bands are generally used as indicators to measure changes in stock prices and are used as indicators to identify average stock prices and volatility. In this paper, the Bollinger Bands proposed are adaptive Bollinger Bands that reflect the trend line according to the characteristics of the sensor data so that abnormal behavior can be detected.
Keywords: anomaly detection; time series data; Bollinger Bands; moving average; open innovation
Title: Semantic R&D Knowledge Map on Semantic Similarity Using Word Embedding
Authors: Sehwan Yoo, Junghyun Yoon, Sanghyun Sung *
Abstract: Purpose/Research Question: Entrepreneurship is one of the areas of social interest today and is recognized as an important subject by people according to the Global Entrepreneurship Monitor report (Singer, S. et al., 2018), and it has been a rapidly developing field of study compared to other research despite the fact that it has only been 30 years since entrepreneurship was taken up as a full-fledged field of study (Cornelius, Beta., 2016). However, due to the fact that this research has been conducted with various and independent areas, it has limitations and cannot be accumulated as an effective knowledge base to support subsequent research (Shane et al., 2000; Ucbasaran et al., 2001). Furthermore, the knowledge of entrepreneurship with innovation could be a critical driving force for modern business development, which means that the feasibility of innovation-driven business development would increase because of a better understanding and analytic skills in the process of strategic planning for future scenarios with various business innovations (Min-Ren Yan, 2010; Dubickis and Gaile, 2017). In this study, in order to overcome the issue and figure out the research trends, we conducted research of the existing R&D knowledge guidance methodology, which consists of data collection, data pre-processing, analytical-scenario planning, and data analyzing. During the standardization process, which is the core data pre-processing process in the development of existing R&D knowledge maps, processing such as capitalization, singularization, and abbreviation is automatically possible for existing morphological similarity, but there is a limit to understanding semantic similarity. For this purpose, we have proposed a methodology for extracting keywords and core sentences from the abstract of the thesis and for analyzing the similarity of sentences by grasping the semantic encoding of sentences by word embedding based on the extracted contents.
Keywords: R&D knowledge map; natural language processing; text embedding; syntactic similarity; entrepreneurship
Title: Efficiency Analysis for Public R&D Management Agencies in South Korea Based on the Data Envelopment Analysis (DEA)
Authors: Byung Yong Hwang *, Sung Hun Park, and Dae-cheol Kim
Abstract: R&D management agencies have been taking on key roles in the national R&D ecosystem. The purpose of this study is to suggest ways to improve the role of R&D management agencies for R&D planning and evaluation. The study analyzes the regulatory system and the relative efficiency of the current use of planning and evaluation costs. The data collection sources include documents, surveys, and interviews with staff members in agencies responsible for national R&D management. By using DEA models, relative efficiency is measured. Based on the analysis results, we present suggestions for improvement in three areas: (a) establishment of the institutional basis; (b) improvement of the budget process; (c) expanding public funding for the stable acquisition of R&D planning and evaluation costs. Finally, future directions and limits of this study are discussed.
Keywords: national innovation system; public R&D management agency; data envelopment analysis; R&D performance
Title: Process of Environmental Impact Assessment with ICT for a Tool for Decision-Making Process
Authors: Minkyung Kim, Sangdon Lee *
Abstract: Purpose/Research Question: Verification by applying the environmental impact assessment decision support algorithm developed in real-world/linear projects, etc. through the verification and demonstration of the integrated decision review support model for environmental impact assessment
Keywords: EIA process; algorithm; public hearing; strategic environment assessment
Title: A Case Study on the Development of the Personal Identification Platform Using Blockchain Technology
Authors: Chang Soo Sung, Dea Soo Choi, Joo Y. Park *
Abstract: Purpose/Research Question: This study conducted a case study on the development process of the personal information management system by utilizing blockchain, a key technology of Industry 4.0. Specifically, we examine the current status of the introduction of blockchain technology and its application using case studies from various perspectives at home and abroad and present the problems and alternatives of the current identity authentication system.
Keywords: blockchain technology; identity authentication system; decentralized identification system; case study