Technological progress and smart therapies: two sides of the same coin

PurposeThis study aims to develop the first Theory of Technological Response and Progress in Chaos (TRPC) and examine the case of technological development during the COVID-19 pandemic. The research objectives of this study were to: identify the key technologies that act as a response mechanism during the chaos event, specifically in the case of COVID-19; examine how technologies evolve, develop and diffuse in an immediate crisis and a chaotic environment; theorise various types and periods of technological response and progress during the emergence of chaos and the stages that unfold; and develop policy-oriented recommendations and establish technological foundations to address subsequent chaos events.Design/methodology/approachThis study used the grounded theory as a methodology with a mixed-method approach that included quantitative and qualitative methods. The authors used the quantitative method to assist with the qualitative step to build the TRPC theory. Accordingly, this study integrated machine learning and text mining approaches to the qualitative data analysis following the steps of the grounded theory approach.FindingsAs a result of the TRPC theory development process, the authors identified three types of technologies (survival, essential and enhancement technologies) and five types of periods (stable, initial, survival-dominant, essential-dominant and enhancement-dominant periods) that are specific to chaos-technology interactions. The policy implications of this study demonstrate that a required technological base and know-how must be established before a chaotic event emerges.Research limitations/implicationsConcerning the limitations of this study, social media data has advantages over other data sources, such as the examination of dynamic areas and analyses of immediate responses to chaos. However, other researchers can examine publications and patent sources to augment the findings concerning scientific approaches and new inventions in relation to COVID-19 and other chaos-specific developments. The authors developed the TRPC theory by studying the COVID-19 pandemic, however, other researchers can utilise it to study other chaos-related conditions, such as chaotic events that are caused by natural disasters. Other scholars can investigate the technological response and progress pattern in other rapidly emerging chaotic events of an uncertain and complex nature to augment these findings.Practical implicationsFollowing the indications of the OECD (2021a) and considering the study conducted by the European Parliamentary Research Service (Kritikos, 2020), the authors identified the key technologies that are significant for chaos and COVID-19 response using machine learning and text intelligence approach. Accordingly, the authors mapped all technological developments using clustering approaches, and examined the technological progress within the immediate chaos period using social media data.Social implicationsThe key policy implication of this study concerns the need for policymakers to develop policies that will help to establish the required technological base and know-how before chaos emerges. As a result, a rapid response can be implemented to mitigate the chaos and transform it into a competitive advantage. The authors also revealed that this recommendation overlaps with the model of dynamic capabilities in the literature (Teece and Pisano, 2003). Furthermore, this study recommends that nations and organisations establish a technological base that specifically includes technologies that bear 3A characteristics. These are the most crucial technologies for the survival- and essential-dominant stages. Moreover, the results of this study demonstrate that chaos accelerates technological progress through the rapid adoption and diffusion of technologies into different fields. Hence, nations and organisations should regard this rapid progress as an opportunity and establish the prior knowledge base and technologies before chaos emerges.Originality/valueThe authors have contributed to the chaos studies and the relationship between chaos and technological development by establishing the first theoretical foundation using the grounded theory approach, hereafter referred to as the TRPC theory. As part of the TRPC theory, the authors present three periods of technological response in the following sequence: survival technology, essential technology and enhancement technology. Moreover, this study illustrates the evolving technological importance and priorities as the periods of technological progress proceed under rapidly developing chaos.

Research and development investment is a necessary resource guarantee for technological innovation and progress. Increasing research and development investment to promote production efficiency and gain competitive advantages is a strategic choice for many state-owned enterprises in China. The R&D investment of state-owned enterprises is the decision result of balancing external market demand and internal resource environment. Research suggests that state-owned enterprises should increase R&D investment in core business areas and strategic emerging areas, strengthen cooperation with external advantageous technological resources, form a virtuous cycle of “R&D - technological progress - dividend generation - R&D”, and achieve long-term sustainable development.

In today’s ever-changing landscape of economy, one of the fundamental problems remains whether market mechanisms are functioning in an efficient way, and which are the variables impacting those levels of efficiency. The main objectives of the present paper are to contribute to a better understanding of market mechanisms, by testing the Efficient market hypothesis on its weak form at a macroeconomic level, and to assess the impact of technological and social progress, measured through different variables, on markets informational efficiency. We use an adapted version of L. Kristoufek si M. Vosvrda (L. Kristoufek, M. Vosvrda, 2013, 184) methodology for Efficiency Index, based on long term memory (using 2 estimators), fractal dimension (using 11 estimators), and entropy (estimated through the approximate entropy), in order to assess the levels of efficiency for 20 market indices from both developed and emerging or frontier economies, from the Eurasia region. Further on, by using the Bayesian Model Averaging (BMA), we study the impact of technological and social progress on markets informational efficiency. Main results of the study reveal the existence of a market dynamics characterized by areas with distinctive levels of “informational efficiency”, within both developed and emerging economies, encompassing a non-negligible link between past and present, persistence or anti-persistence, and a high data complexity. Moreover, while studying the relationship between market efficiency and social and technological progress, we observe that variables such as Government Effectiveness, or Control of Corruption, have a positive impact on the levels of efficiency of capital markets, while most of the technological progress estimators (amongst which Computer, communications and other services (% of commercial service exports), or Individuals using the Internet (% of population)), have a negative impact, translated into a decrease of informational market efficiency on the short run (the rise of high frequency trading).

Research background: Various methods for technological progress assessment and evaluation exist in the context of economic development. Each of the methods possesses distinct advantages and disadvantages in analysis of technological progress fluctuations. For most neoclassical growth theories, technological progress measures are included as exogenous variables, thus excluding evaluation of factors influencing technological progress variation throughout time. Purpose of the article: The aim of this article is to offer improvements on classical technological progress evaluation methodologies for manufacturing industries, separating effect of intersectoral technological progress spillover effect from internal factors influencing technological progress growth and perform analysis in the case of Lithuanian manufacturing industry. Methods: Earlier research papers used linear time series regression and vector autoregression methods to assess technological progress values and define equations explaining effect of different manufacturing level indicators on technological progress measure growth. This research paper uses results of previously mentioned methods and performs simulation analysis applying agent-based modelling framework. Findings & value added: The conducted vector autoregression analysis has showed that two variables which influence technological progress most significantly are labor productivity measure and gross profit value. Sensitivity analysis emphasizes that effect of these two variables on technological progress growth is substantially different. Increase in gross profit value affects technological progress growth for wider range of sectors from Lithuanian manufacturing industry (15 out of 18 analyzed sectors? technological progress measure values are affected by changes in gross profit, while changes in labor productivity influence technological progress values in the case of 9 sectors). Rising gross profit values also produce intersectoral technological progress spillover effect more significantly, while growth in labor productivity measure has stronger effect on technological progress fluctuations for sectors which are able to exploit this effect. Presented research suggests improved methodology for intersectoral technological progress spillover effect assessment in the context of manufacturing industries.

With the continuous development of network technology, network technology has been applied to various fields of social life and production. The development of Library and information industry is advancing with the progress of technology and has brought about great changes. How to face the challenge of the progress of network technology for Library and information science, and how to promote the reform and innovation of Library and information science is an important problem at present. This paper aims to study the challenges faced by library and Information Science in the era of network, and look forward to the future reform and innovation direction and path of Library and information science through the current situation. In this paper, qualitative and quantitative research methods combined with CO word analysis are used to sort out the interdisciplinary research topics of Library and information science, as well as the changes and comparison of Library and information science research methods in the era of network, so as to get the development trend and direction of Library and Information Science in China. Research and analysis show that the main research of Library and information science focuses on "computer and computer application". With the continuous progress of network technology, there are more and more network technologies involved in Library and information institutions, which will produce more and more research topics. At the same time, the research methods of Library and Information Science in China are also out of date. Only by applying computer technology Only by applying it to the research and enriching the existing researchers to construct the network of information resources, can the data statistics and analysis be carried out with the highest efficiency, so as to realize the positive promotion for the discipline and other disciplines. In the network era, the future development of Library and information science requires us to make steady progress and comply with the new requirements and changes of the network era, so as to make the development of Library and information science more complete and adapt to the higher requirements of the network era.

In a knowledge-based economy, technical progress is ultimately based upon progress in science and upon subsequent progress in technology. This linkage between science and technology has been called “scientific technology” - continuing progress in technology that directly uses progress in science. Scientific technology was the technical basis of the first industrial revolution in the eighteenth century and has continued to provide the technical basis for economic development in the world. During the twentieth century, research universities became the locus of scientific progress while industrial research was the locus of technological progress. At the same time, modern governmental R&D support became a major source of funds for scientific research and for much of the early development of scientific technology research. Thus universities, industry, and government R&D all have become important for fostering continuing progress in scientific technology for a knowledge-based economy.

Technological activity, taken in a broad craft sense, is not new to primary schools. What is new is its organisation as a serious curriculum subject in which pupils are expected to make valuable progress. Arguing about technology-as-education must include some understanding of what it can offer of wide value to successful students. Unfortunately those who have carried out empirical research in the field of primary technology have been unable to specify what such valuable progression might look like. There are just two rather limited sources of information relevant to development and progress in technology — cognitive psychology and teacher action research. Neither of these is easy to use as they stand because they are either unconnected with the act of teaching, or on a very small and personal scale. However this paper argues that, taken together, they are beginning to show that teaching has valuable and specific tasks to carry out, which can help pupils make recognisable progress in primary technology.

The electric vehicle (EV) technological supply chain progresses when demand (pull) aligns with supply (push) to perform as a technology delivery system. Actors, institutions, and networks interconnect the technological supply chain with innovation as responses to external pressures to produce and deliver technology products/services. The literature separately examined the progress from a delivery perspective (linking the demand and supply network) and a systems perspective that examines technological change as a socio-technical system. Technological progress requires changes aligning push and pull or one feeding into the other. The ‘motors of innovation’ that shape the innovation system are used in systems dynamics modeling linking technological changes and progress. This study uses ‘motors of innovation’ to combine the two perspectives and uses interconnectedness to examine the alignment of push and pull and the resulting delivery phenomena. The phenomena require studying it in its settings with diverse heuristic and analytic views. Therefore, this study uses case study methodology and selects multiple Indian EV cases comprising all vehicle segments in a government direct market scenario. It makes two contributions to technological progress: one defines the combined delivery and systems perspective and includes interconnectedness. The other is moving knowledge to a broad scope and expertise and striving for interconnectedness with other systems. Further insights are possible with cases that display better technological progress, as findings noted poor interconnectedness with limited technological capability and infrastructure.

This chapter focuses on technological progress and its relationship with population growth. Although we begin with the Malthusian theory, it is important to note that Malthus did not understand the importance of technological progress in society at the time. Kremer (Q J Econ 108:681–716, 1993) and other economists have stressed that it is possible to observe a close relationship between population growth and production technology, and Boserup (The conditions of agricultural progress. Aldine Publishing Company, Chicago, 1965) has pointed out that Malthus ignored the positive consequences of population growth in the long run. We define technological progress in an economic sense and emphasize that such progress has become an engine of economic growth for the modern economy. The important question to be posed is, “Does the size of population affect technological progress?” The answer is that a large population will generate many ideas that could bring about rapid technological progress. In addition, technological progress eases the constraints triggered by population growth by increasing the production of economic resources. Furthermore, we discuss the scale effect which means that a larger population would generate a rapid growth of population by mediating technological progress. Next, in developed countries, declining fertility rates have been widely observed and identified as causing population declines in the future. This phenomenon has raised an important point to discuss concerning the relationship between technological progress and population. Lastly, we conclude that the relationship between population size and technological progress encompasses complicated mutually exclusive effects. Specifically, technological progress leads to economic prosperity, which results in reduced fertility and population growth, while population size has a positive effect on technological progress. In the appendices of this chapter, we summarize the Kremer’s theoretical model and provide a simple survey of endogenous growth theory including population dynamics.

Effects of heterogeneous technological progress on haze pollution: Evidence from China

Background: In the context of the deep integration of the tourism industry with informatization and technological progress, exploring the mutual influences and dynamic interactions among tourism development, technological progress, and informatization holds significant value for achieving low-carbon sustainable development goals. Methods: Based on provincial statistical data from China between 2008 and 2020, this study employs a panel vector autoregression (PVAR) model to analyze the interactions, characteristics, and trends among informatization, technological progress, and tourism industry development. Results: First, there exists a complex dynamic interaction mechanism among informatization, technological progress, and tourism development. Informatization significantly promotes technological progress and tourism development, while technological progress provides technical support for both informatization and tourism. However, the direct impact of tourism on informatization is relatively limited, with a more pronounced effect on technological progress. Second, impulse response analysis reveals the dynamic adjustment paths among variables: tourism development responds strongly to shocks from informatization and technological progress in the initial stages, followed by gradual attenuation and stabilization. Similarly, informatization shows a strong initial response to shocks from technological progress, which then gradually diminishes and stabilizes. When responding to shocks from tourism, informatization exhibits an inverted U-shaped curve, first rising and then declining. Technological progress also demonstrates an inverted U-shaped curve in response to shocks from tourism and informatization. Third, variance decomposition shows that in the early stages, the fluctuations of system variables are primarily self-explanatory, while dynamic interactions among variables emerge and stabilize over the long term. This study provides policy insights for governments and industry stakeholders on enhancing tourism development, informatization, and technologicalprogress under the framework of sustainable development.

In this paper, a nonparametric method is used to measure the total factor productivity (TFP) growth index in Chinese agriculture from 1981 to 2017, and the factor bias of technological progress is identified based on the theory of induced technological progress. Then, according to the degree of dependence of technological progress on fertiliser, biased technological progress is divided into green-biased technological progress and pollution-biased technological progress, and then empirical test the factors allocation structure that induce and promote green-biased technological progress. The results show that China's agricultural TFP has undergone three stages of accelerated growth, negative growth and fluctuation, and the growth momentum has undergone three transformations, which are jointly driven by technological efficiency and technological progress, dominated by technological progress and dominated by technological efficiency. Biased technological progress has contributed to the long-term growth of agricultural TFP in most regions of China, but it is mainly biased towards capital-using and fertiliser-using. The labour/capital ratio and the capital/fertiliser ratio are increased, reducing the capital/soil ratio, which can induce and promote green-biased technological progress while suppressing pollution-biased technological progress. The mechanism test results show that increasing labour input can indirectly promote green technological progress by reducing mechanisation.

Global value chains, technological progress, and environmental pollution: Inequality towards developing countries

Technology affects economic growth and development in many ways. It comes in many forms and affects firm growth and industry evolution. Three specific economic meanings of technology and technological progress have been emphasized in dynamic economics. First, it measures the dynamic shift over time of the production frontier, i.e., the way the various inputs are utilized to produce outputs over time. Technological progress may be partly embodied in the individual inputs like labor and capital, or it may reflect the joint productivity effects of some or all inputs. Second, technology may take the form of new research ideas and knowledge as human capital.

On the basis of the case study of the selected government-linked companies (GLCs), this paper examines the technological stock progress and further assesses its implication for growth. A synthesized framework of analysis (using technological stock and logistic growth function) is proposed to highlight the virtuous cycle between R&D investment, technology stock and growth. The results suggest that two of the selected firms (Proton and Golden Hope), indeed, showed better technological progress. However, Proton seems to achieve the maturity stage of technology and further needs to enhance its technology capability to drive its performance in the future. In contrast, TNB is found to lack the technological development to promote performance. The results, on the one hand, suggest that technology development is mostly progressive with high returns in the areas where the country has definite comparative advantage (e.g. oil palm) and when better partnership exists. On the other hand, in a highly protective market, the technological progress is slow – the case of energy sector – and contribution of technology progress towards growth is in lack – as in the case of automotive sector. Case comparison suggests that attempts to develop technology require competitive market with less government protective measures.