arXiv subjects

Mario Coccia

Publications and source records attributed to Mario Coccia.

At least 19 recordsLinked to original sources

arXiv2022

New technological trajectories and research directions in Cloud Computing Technology, 2004-2021

The goal of this study is to explore emerging trends in cloud computing technology that can support an economic and social change. We apply the methods of entity linking, which links word strings to entities from a knowledge base, to extract main keywords in cloud computing from accumulated publications from 2004 to 2021. Results suggest that in cloud computing research, Internet of things has an accelerated technological and scientific growth compared to the other topics. Other critical research fields that support the evolution of cloud computing are mathematical optimization and virtual machine. These findings reveal a technological competition between Cloud systems infrastructure, hardware development side, and computing and software development to play the main role in technological evolution of Cloud Computing. Moreover, this study shows that technological development of virtual machines and computing device can be of critical importance to foster an economic and technological change in many sectors. However, the implementation of cloud computing has to be supported by skill development, organizational change, and adopter engagement, to foster the management and the diffusion of cloud technologies and the exploitation of cloud-based infrastructures for competitive advantage of firms in fast-changing markets. This study can provide main information to extend the knowledge having theoretical implications to explain characteristics of the evolution of science and technology in this field of research and practical implications of innovation management for the appropriate allocation of resources towards new technological trajectories in cloud computing having a potential of growth and beneficial impact in society.

cs.DC↗

arXiv2022

Sensor technologies in cancer research for new directions in diagnosis and treatment: and exploratory analysis

The goal of this study is an exploratory analysis concerning main sensor technologies applied in cancer research to detect new directions in diagnosis and treatments. The study focused on types of cancer having a high incidence and mortality worldwide: breast, lung, colorectal and prostate. Data of the Web of Science (WOS) core collection database are used to retrieve articles related to sensor technologies and cancer research over 1991-2021 period. We utilized Gephi software version 0.9.2 to visualize the co-word networks of the interaction between sensor technologies and cancers under study. Results show main clusters of interaction per typology of cancer. Biosensor is the only type of sensor that plays an essential role in all types of cancer: breast cancer, lung cancer, prostate cancer, and colorectal cancer. Electrochemical sensor is applied in all types of cancer under study except lung cancer. Electrochemical biosensor is used in breast cancer, lung cancer, and prostate cancer research but not colorectal cancer. Optical sensor can also be considered one of the sensor technologies that significantly is used in breast cancer, prostate cancer, and colorectal cancer. This study shows that this type of sensor is applied in more diversified approaches. Moreover, the oxygen sensor is mostly studied in lung cancer and breast cancer due to the usage in breath analysis for the treatment process. Finally, Cmos sensor is a technology used mainly in lung cancer and colorectal cancer. Results here suggest new directions for the evolution of science and technology of sensors in cancer research to support innovation and research policy directed to new technological trajectories having a potential of accelerated growth and positive social impact for diagnosis and treatments of cancer.

eess.SP↗

arXiv2020

Cyclical phenomena in technological change

The process of technological change can be regarded as a non-deterministic system governed by factors of a cumulative nature that generate cyclical phenomena. In this context, the process of growth and decline of technology can be systematically analyzed to design best practices for technology management of firms and innovation policy of nations. In this perspective, this study focuses on the evolution of technologies in the U.S. recorded music industry. Empirical findings reveal that technological change in the sector under study here has recurring fluctuations of technological innovations. In particular, cycle of technology has up wave phase longer than down wave phase in the process of evolution in markets before it is substituted by a new technology. Results suggest that radical innovation is one of the main sources of cyclical phenomena for industrial and corporate change, and as a consequence, economic and social change.

econ.GN↗

arXiv2020

How sustainable environments have reduced the diffusion of coronavirus disease 2019: the interaction between spread of COVID-19 infection, polluting industrialization, wind (renewable) energy

This study endeavors to explain the relation between air pollution and particulate compounds emissions, wind resources and energy, and the diffusion of COVID-19 infection to provide insights of sustainable policy to prevent future epidemics. The statistical analysis here focuses on case study of Italy, one of the countries to experience a rapid increase in confirmed cases and deaths. Results reveal two main findings: 1) cities in regions with high wind speed and a high wind energy production in MW have a lower number of infected individuals of COVID-19 infection and total deaths; 2) cities located in hinterland zones (mostly those bordering large urban conurbations) with high polluting industrialization, low wind speed and less cleaner production have a greater number of infected individuals and total deaths. Hence, cities with pollution industrialization and low renewable energy have also to consider low wind speed and other climatological factors that can increase stagnation of the air in the atmosphere with potential problems for public health in the presence of viral agents. Results here suggest that current pandemic of Coronavirus disease and future epidemics similar to COVID-19 infection cannot be solved only with research and practice of medicine, immunology and microbiology but also with a proactive strategy directed to interventions for a sustainable development. Overall, then, this study has to conclude that a strategy to prevent future epidemics similar to COVID-19 infection must also be based on sustainability science to support a higher level of renewable energy and cleaner production to reduce polluting industrialization and, as result, the factors determining the spread of coronavirus disease and other infections in society.

physics.soc-ph↗

arXiv2020

Effects of the institutional change based on democratization on origin and diffusion of technological innovation

Political systems shape institutions and govern institutional change supporting economic performance, production and diffusion of technological innovation. This study shows, using global data of countries, that institutional change, based on a progressive democratization of countries, is a driving force of inventions, adoption and diffusion of innovations in society. The relation between technological innovation and level of democracy can be explained with following factors: higher economic freedom in society, effective regulation, higher economic and political stability, higher investments in R&D and higher education, good economic governance and higher level of education system for training high-skilled human resources. Overall, then, the positive associations between institutional change, based on a process of democratization, and paths of technological innovation can sustain best practices of political economy for the development of economies in the presence of globalization and geographical expansion of markets.

econ.GN↗

arXiv2019

How do scientific disciplines evolve in applied sciences? The properties of scientific fission and ambidextrous scientific drivers

One of the fundamental questions in science is how scientific disciplines evolve and sustain progress in society. No studies to date allows us to explain the endogenous processes that support the evolution of scientific disciplines and emergence of new scientific fields in applied sciences of physics. This study confronts this problem here by investigating the evolution of experimental physics to explain and generalize some characteristics of the dynamics of applied sciences. Empirical analysis suggests properties about the evolution of experimental physics and in general of applied sciences, such as: a) scientific fission, the evolution of scientific disciplines generates a process of division into two or more research fields that evolve as autonomous entities over time; b) ambidextrous drivers of science, the evolution of science via scientific fission is due to scientific discoveries or new technologies; c) new driving research fields, the drivers of scientific disciplines are new research fields rather than old ones; d) science driven by development of general purpose technologies, the evolution of experimental physics and applied sciences is due to the convergence of experimental and theoretical branches of physics associated with the development of computer, information systems and applied computational science. Results also reveal that average duration of the upwave of scientific production in scientific fields supporting experimental physics is about 80 years. Overall, then, this study begins the process of clarifying and generalizing, as far as possible, some characteristics of the evolutionary dynamics of scientific disciplines that can lay a foundation for the development of comprehensive properties explaining the evolution of science as a whole for supporting fruitful research policy implications directed to advancement of science and technological progress in society.

econ.GN↗

arXiv2019

A new technological system to revolutionize the management of valvular heart diseases: transcatheter aortic valve for the treatment of aortic stenosis

The goal of this study is a technology analysis of a revolution for the management of valvular heart diseases given by new technological system based on transcatheter artificial aortic valve, a delivery catheter and a loading system for the treatment of aortic stenosis (a narrowing of the aortic valve because of calcium build up that restricts blood flow to aorta, the body's main artery) in patients at intermediate and greater risk for surgical therapy. In particular, this study analyzes the technological trajectories of new technology of transcatheter aortic valve implantation (TAVI) in relation to the established technology of surgical aortic valve replacement (SAVR). To explore the emerging technology of TAVI for valvular heart diseases, a model is applied to show how new TAVI technology is substituting established technologies of SAVR to revolutionize the management of aortic stenosis in cardiology. Statistical analyses reveal the sharp increase of the scientific production of TAVI that has a coefficient of growth as function of time equal to 0.40 (p<.001) versus a coefficient for SAVR technology of 0.10 (p<.001). This finding suggests a technological forecasting that TAVI will be the dominant technology for the treatment of patients with valvular heart diseases. Overall, then, this study shows that new technology of transcatheter aortic valve implantation (TAVI) introduced in 2002 is growing in terms of scientific, inventive and innovative activity to revolutionize the management of aortic stenosis in cardiology worldwide.

physics.med-ph↗

arXiv2019

A new concept of technology with systemic-purposeful perpsective: theory, examples and empirical application

Although definitions of technology exist to explain the patterns of technological innovations, there is no general definition that explain the role of technology for humans and other animal species in environment. The goal of this study is to suggest a new concept of technology with a systemic-purposeful perspective for technology analysis. Technology here is a complex system of artifact, made and_or used by living systems, that is composed of more than one entity or sub-system and a relationship that holds between each entity and at least one other entity in the system, selected considering practical, technical and_or economic characteristics to satisfy needs, achieve goals and_or solve problems of users for purposes of adaptation and_or survival in environment. Technology T changes current modes of cognition and action to enable makers and_or users to take advantage of important opportunities or to cope with consequential environmental threats. Technology, as a complex system, is formed by different elements given by incremental and radical innovations. Technological change generates the progress from a system T1 to T2, T3, etc. driven by changes of technological trajectories and technological paradigms. Several examples illustrate here these concepts and a simple model with a preliminary empirical analysis shows how to operationalize the suggested definition of technology. Overall, then, the role of adaptation (i.e. reproductive advantage) can be explained as a main driver of technology use for adopters to take advantage of important opportunities or to cope with environmental threats. This study begins the process of clarifying and generalizing, as far as possible, the concept of technology with a new perspective that it can lay a foundation for the development of more sophisticated concepts and theories to explain technological and economic change in environment.

econ.GN↗

arXiv2019

Killer Technologies: the destructive creation in the technical change

Killer technology is a radical innovation, based on new products and/or processes, that with high technical and/or economic performance destroys the usage value of established techniques previously sold and used. Killer technology is a new concept in economics of innovation that may be useful for bringing a new perspective to explain and generalize the behavior and characteristics of innovations that generate a destructive creation for sustaining technical change. To explore the behavior of killer technologies, a simple model is proposed to analyze and predict how killer technologies destroy and substitute established technologies. Empirical evidence of this theoretical framework is based on historical data on the evolution of some example technologies. Theoretical framework and empirical evidence hint at general properties of the behavior of killer technologies to explain corporate, industrial, economic and social change and to support best practices for technology management of firms and innovation policy of nations. Overall, then, the proposed theoretical framework can lay a foundation for the development of more sophisticated concepts to explain the behavior of vital technologies that generate technological and industrial change in society.

econ.GN↗

arXiv2019

Artificial intelligence technology in oncology: a new technological paradigm

Artificial Intelligence (AI) technology is based on theory and development of computer systems able to perform tasks that normally require human intelligence. In this context, deep learning is a family of computational methods that allow an algorithm to program itself by learning from a large set of examples that demonstrate the desired behavior. Application of these methods to medical imaging can assist pathologists in the detection of cancer subtype, gene mutations and/or metastases for applying appropriate therapies. The purpose of this study is to show the emerging application of AI in medical imaging to detect lung and breast cancer. Moreover, this study shows the comparative evolutionary pathways of this emerging technology for three critical cancers: lung, breast and thyroid. A main finding of this study is the recognition that, since the late 1990, the sharp increase of technological trajectories of AI technology applied in cancer imaging seems to be driven by high rates of mortality of some types of cancer (e.g., lung and breast) in order to find new techniques for a more accurate detection, characterization and monitoring as well as to apply efficiently anticancer therapies that increase the progression-free survival of patients: the so-called mortality-driven AI technological trajectories. Results also suggest that this new technology can generate a technological paradigm shift for diagnostic assessment of any cancer type. However, application of these methods to medical imaging requires further assessment and validation to assist pathologists to increase the efficiency of their workflow in both routine tasks and critical cases of diagnostics.

cs.CY↗

arXiv2019

Technological Parasitism

Technological parasitism is a new theory to explain the evolution of technology in society. In this context, this study proposes a model to analyze the interaction between a host technology (system) and a parasitic technology (subsystem) to explain evolutionary pathways of technologies as complex systems. The coefficient of evolutionary growth of the model here indicates the typology of evolution of parasitic technology in relation to host technology: i.e., underdevelopment, growth and development. This approach is illustrated with realistic examples using empirical data of product and process technologies. Overall, then, the theory of technological parasitism can be useful for bringing a new perspective to explain and generalize the evolution of technology and predict which innovations are likely to evolve rapidly in society.

econ.GN↗

arXiv2018

Socioeconomic driving forces of scientific research

Why do nations produce scientific research? This is a fundamental problem in the field of social studies of science. The paper confronts this question here by showing vital determinants of science to explain the sources of social power and wealth creation by nations. Firstly, this study suggests a new general definition of science and scientific research that synthetizes previous concepts and endeavors to extend them: Science discovers the root causes of phenomena to explain and predict them in a context of adaptation of life to new economic and social bases, whereas scientific research is a systematic process, applying methods of scientific inquiry, to solve consequential problems, to satisfy human wants, to take advantage of important opportunities and/or to cope with environmental threats. In particular, science and scientific research are driven by an organized social effort that inevitably reflect the concerns and interests of nations to achieve advances and discoveries that are spread to the rest of humankind. This study reveals that scientific research is produced for social and economic interests of nations (power, wealth creation, technological superiority, etc.), rather than philosophical inquiries. A main implication of this study is that the immense growth of science in modern society is not only due to activity of scientists but rather to general social efforts of nations to take advantage of important opportunities and/or to cope with environmental threats, such as war. Empirical evidence endeavors to support the sources of scientific research for nations, described here. Finally, relationships between R&D investment and productivity, and research policy implications are discussed.

q-fin.GN↗

arXiv2018

National debts and government deficits within European Monetary Union: Statistical evidence of economic issues

This study analyzes public debts and deficits between European countries. The statistical evidence here seems in general to reveal that sovereign debts and government deficits of countries within European Monetary Unification-in average- are getting worse than countries outside European Monetary Unification, in particular after the introduction of Euro currency. This socioeconomic issue might be due to Maastricht Treaty, the Stability and Growth Pact, the new Fiscal Compact, strict Balanced-Budget Rules, etc. In fact, this economic policy of European Union, in phases of economic recession, may generate delay and rigidity in the application of prompt counter-cycle (or acyclical) interventions to stimulate the economy when it is in a downturn within countries. Some implications of economic policy are discussed.

econ.GN↗

arXiv2018

How do public research labs use funding for research? A case study

This paper discusses how public research organizations consume funding for research, applying a new approach based on economic metabolism of research labs, in a broad analogy with biology. This approach is applied to a case study in Europe represented by one of the biggest European public research organizations, the National Research council of Italy. Results suggest that funding for research (state subsidy and public contracts) of this public research organization is mainly consumed for the cost of personnel. In addition, the analysis shows a disproportionate growth of the cost of personnel in public research labs in comparison with total revenue from government. In the presence of shrinking public research lab budgets, this organizational behavior generates inefficiencies and stress. R&D management and public policy implications are suggested for improving economic performance of public research organizations in turbulent markets.

econ.GN↗

arXiv2018

The laws of the evolution of research fields

A fundamental question in the field of social studies of science is how research fields emerge, grow and decline over time and space. This study confronts this question here by developing an inductive analysis of emerging research fields represented by human microbiome, evolutionary robotics and astrobiology. In particular, number of papers from starting years to 2017 of each emerging research field is analyzed considering the subject areas (i.e., disciplines) of authors. Findings suggest some empirical laws of the evolution of research fields: the first law states that the evolution of a specific research field is driven by few scientific disciplines (3- 5) that generate more than 80% of documents (concentration of the scientific production); the second law states that the evolution of research fields is path-dependent of a critical discipline (it can be a native discipline that has originated the research field or a new discipline emerged during the social dynamics of science); the third law states that a research field can be driven during its evolution by a new discipline originated by a process of specialization within science. The findings here can explain and generalize, whenever possible some properties of the evolution of scientific fields that are due to interaction between disciplines, convergence between basic and applied research fields and interdisciplinary in scientific research. Overall, then, this study begins the process of clarifying and generalizing, as far as possible, the properties of the social construction and evolution of science to lay a foundation for the development of sophisticated theories.

econ.GN↗

arXiv2018

Critical analysis of human progress: Its negative and positive sides in the late-capitalism

The concept of progress has characterized human society from millennia. However, this concept is elusive and too often given for certain. The goal of this paper is to suggest a general definition of human progress that satisfies, whenever possible the conditions of independence, generality, epistemological applicability and empirical correctness. This study proposes, within a pragmatic approach, human progress as an inexhaustible process driven by an ideal of maximum wellbeing of purposeful people which, on attainment of any of its goals or objectives for increasing wellbeing, then seek another consequential goal and objective, endlessly, which more closely approximates its ideal fixed in new socioeconomic contexts over time and space. The human progress, in the global, capitalistic, and post-humanistic Era, improves the fundamental life-interests represented by health, wealth, expansion of knowledge, technology and freedom directed to increase wellbeing throughout the society. These factors support the acquisition by humanity of better and more complex forms of life. However, this study shows the inconsistency of the equation economic growth= progress because human progress also generates, during its continuous process without limit, negative effects for human being, environment and society.

q-fin.GN↗

arXiv2018

Measurement of the evolution of technology: A new perspective

A fundamental problem in technological studies is how to measure the evolution of technology. The literature has suggested several approaches to measuring the level of technology (or state-of-the-art) and changes in technology. However, the measurement of technological advances and technological evolution is often a complex and elusive topic in science. The study here starts by establishing a conceptual framework of technological evolution based on the theory of technological parasitism, in broad analogy with biology. Then, the measurement of the evolution of technology is modelled in terms of morphological changes within complex systems considering the interaction between a host technology and its subsystems of technology. The coefficient of evolutionary growth of the model here indicates the grade and type of the evolutionary route of a technology. This coefficient is quantified in real instances using historical data of farm tractor, freight locomotive and electricity generation technology in steam-powered plants and internal-combustion plants. Overall, then, it seems that the approach here is appropriate in grasping the typology of evolution of complex systems of technology and in predicting which technologies are likeliest to evolve rapidly.

econ.GN↗

arXiv2017

A New Classification of Technologies

This study here suggests a classification of technologies based on taxonomic characteristics of interaction between technologies in complex systems that is not a studied research field in economics of technical change. The proposed taxonomy here categorizes technologies in four typologies, in a broad analogy with the ecology: 1) technological parasitism is a relationship between two technologies T1 and T2 in a complex system S where one technology T1 benefits from the interaction with T2, whereas T2 has a negative side from interaction with T1; 2) technological commensalism is a relationship between two technologies in S where one technology benefits from the other without affecting it; 3) technological mutualism is a relationship in which each technology benefits from the activity of the other within complex systems; 4) technological symbiosis is a long-term interaction between two (or more) technologies that evolve together in complex systems. This taxonomy systematizes the typologies of interactive technologies within complex systems and predicts their evolutionary pathways that generate stepwise coevolutionary processes of complex systems of technology. This study here begins the process of generalizing, as far as possible, critical typologies of interactive technologies that explain the long-run evolution of technology. The theoretical framework developed here opens the black box of the interaction between technologies that affects, with different types of technologies, the evolutionary pathways of complex systems of technology over time and space. Overall, then, this new theoretical framework may be useful for bringing a new perspective to categorize the gradient of benefit to technologies from interaction with other technologies that can be a ground work for development of more sophisticated concepts to clarify technological and economic change in human society.

cs.CY↗