Technological Change Research Articles

Technological Progress and Wage Share of Old Workers

Abstract Technological progress may be less beneficial for older workers than younger workers. In this paper, we empirically examine the relationship between technological change and the wage share of old workers. More specifically, we look at five different types of technological advancement using data from 30 European and Asian countries at the forefront of global population aging. Our findings indicate that recent technological developments centered on information and communication technology, software, and robots do not adversely affect old workers. One possible explanation is that old workers may be more open to and capable of learning new technologies than widely presumed.

Back-propagation ANN to Predict Cleanliness and Quality of Cotton Spinning Preparatory Output: A Comprehensive Research

Background: Modern spinning preparatory has undergone drastic technological changes, but still, individual’s expertise-based decisions govern the complex and non-linear multivariant relationships prevailing amongst raw material (cotton) variables, machine variables, process variables (waste), and product (card sliver) quality. The scientifically precise prediction regarding the cleanliness and quality of card sliver and waste control for the given inputted cotton variables processed on the state-of-the-art machinery setup without waiting for the production and testing of card sliver is still impossible. Methods: The present work describes the use of Aritificial Neural Networks (ANN) for ruling out these limitations on scientific grounds. A complex system targeted at ANN was developed using the "newff" function on the mill's five-year database. Single-group ANN was initially designed to determine the influence of inherent variations in raw cotton fibre properties and trash content on blow room and card performance. A multi-group approach of ANN was developed at a later stage to define the influence of complex interactions amongst various fibre properties on three main quality measures considered at blow room and carding, viz., i) influence of blow room and card on fibre length properties, ii) fibre damage at blow room or improvement at card, and iii) degree of cleanliness of the output material. Results: Reverse modelling for both groups was also successfully designed to demarcate feed cotton quality and cleanliness requirements for targeted blow room or card cleaning performance. Conclusion: A high level of positive endurance was observed for all ANNs. Multigroup networking has proven to be more precise than single group networking.

Critical thinking and artificial intelligence in tandem: A nursing perspective

The human race is forced to engage in a very rapid adaptation process whenever it is confronted with technological change in any sphere of life. The unabated progress of artificial intelligence (AI) has also impacted the field of critical thinking. It is fascinating that critical thinking, an essential component of intellectual intelligence in nursing, seems to be disrupted by an artificial brain-alike machine that can automatically analyze and synthesize a series of contexts. This has been an improvisation of ideas of intellectual intelligence for a very long time. Perspectives on both sides of the coin bring up interesting questions about the role that AI will play in the future, such as whether it will disrupt the critical thinking skills of nurses or whether it may be engaged as a tool to increase the critical thinking skills capability, especially in the fields of nursing care.

Coordination dynamics between fuel cell and battery technologies in the transition to clean cars

Significant progress reconciling economic activities with a stable climate requires radical and rapid technological change in multiple sectors. Here, we study the case of the automotive industry's transition to electric vehicles, which involved choosing between two different technologies: fuel cell electric vehicles (FCEVs) or battery electric vehicles (BEVs). We know very little about the role that such technological uncertainty plays in shaping the strategies of firms, the efficacy of technological and climate policies, and the speed of technological transitions. Here, we explain that the choice between these two technologies posed a global and multisectoral coordination game, due to technological complementarities and the global organization of the industry's markets and supply chains. We use data on patents, supply-chain relationships, and national policies to document historical trends and industry dynamics for these two technologies. While the industry initially focused on FCEVs, around 2008, the technological paradigm shifted to BEVs. National-level policies had a limited ability to coordinate global players around a type of clean car technology. Instead, exogenous innovation spillovers from outside the automotive sector played a critical role in solving this coordination game in favor of BEVs. Our results suggest that global and cross-sectoral technology policies may be needed to accelerate low-carbon technological change in other sectors, such as shipping or aviation. This enriches the existing theoretical paradigm, which ignores the scale of interdependencies between technologies and firms.

The Main Features and Microbiota Diversity of Fermented Camel Milk

Fermented camel milk, named shubat in Central Asia, is historically and culturally important because it is mainly consumed by Kazakh people who live not only in Kazakhstan but also in close neighboring countries. However, despite its cultural and dietetic significance for this local population, research on its composition and processing technology and the richness of its microflora is relatively scarce. The present review of this product, which is an important beverage in the Kazakh culture, provides up-to-date information regarding its main components and their variability according to different factors, surveys recent changes in the processing technologies for making it using modern techniques, and explores the biodiversity of its microflora. It was reported that the protein, vitamin C, and calcium contents in shubat vary between 1.19 and 5.63%, 28 and 417 mgL−1, and 1.03 and 1.88 gL−1. The lactose content totally disappears. Shubat contains a complex microbial consortium that contributes to its strong reputation for health benefits, but a scientific demonstration of these claims has only been partially achieved.

An unplugged remix of culturally responsive computing for early childhood education

AbstractDespite a growing movement towards expanding computer science education in PreK‐12, gaps in computing opportunities along lines of race, ethnicity, class, and gender have widened. Emergent theories and practices related to culturally responsive computing show promise in addressing this gap; however, little is known about engaging Black, Latinx, and Indigenous preschoolers in computer science. In this paper, we utilized qualitative content analyses to explore how an early childhood computer science curriculum created opportunities for young Black and Latinx preschoolers to develop computational thinking skills while engaging in culturally responsive computing. Overwhelmingly, we found the curriculum, co‐developed with educators and caregivers, emphasized unplugged tools and coding activities to support computational thinking. These unplugged opportunities positioned children as innovators with technology and technosocial change agents, in developmentally‐appropriate, play‐based ways. Findings demonstrate a need to emphasize the value of unplugged tools and coding activities in order to support computational thinking and align the goals of culturally responsive computing with the unique needs of young children. We discuss implications for a theory of culturally responsive computing specifically for early childhood education.

Interior Scene Coloring Design Model Combining Improved K-means and SAA

Due to technological progress and changes in people’s aesthetic standards, traditional design models need to be constantly broken through, seeking more efficient and accurate design methods. Seeking effective design models to improve design efficiency and prediction accuracy is an important task. Therefore, this study proposes an indoor scene coloring design model that combines improved K-means clustering and simulated annealing algorithm for this important task. Based on the analysis of indoor scene coloring, particle swarm optimization algorithm is used to optimize K-means clustering to achieve color classification. Combined with simulated annealing algorithm, adaptive adjustment of lighting conditions is achieved to enhance the naturalness and realism of coloring. These results confirmed that the proposed method had the highest average F-value, with an average F-value of 92.524 and 143.601 on both datasets, respectively. The average ARI values were 0.361 and 0.897, respectively. The designed algorithm performed the best and converged faster than other three. Therefore, the proposed method can effectively ensure the consistency between the distribution of data objects after clustering and the actual situation. For indoor scene coloring design, it has important practical significance and provides new possible paths for improving design efficiency and prediction accuracy.

A Values-led Approach to Technological Change

A Values-led Approach to Technological Change

The Fusion of Minds: Navigating the Confluence of AI, ML, and Psychology in the Digital Era

In an era dominated by rapid technological change, the fusion of Artificial Intelligence (AI), Machine Learning (ML), and Psychology stands as a cornerstone of digital innovation, offering profound transformations across various industries. This paper examines the intricate synergies and ethical dimensions of integrating AI and ML with psychological principles, showcasing their collective capacity to reshape human interactions and decision-making processes in the digital landscape. We explore foundational concepts, detail the progressive evolution of these technologies, and discuss their current applications in creating personalized user experiences. Through a rigorous analysis, we address the ethical imperatives and challenges that arise, emphasizing the need for responsible innovation while harnessing the power of data-driven insights. Our interdisciplinary approach not only reveals the transformative potential of AI and ML when intertwined with psychology but also advocates for a harmonious integration that respects human cognitive and emotional dimensions. This exploration aims to guide stakeholders through the complexities of these technologies, paving the way for ethical practices and innovative solutions in the digital era.

თანამედროვე მიდგომები საბანკო რეგულირებისადმი ციფრული ტექნოლოგიების განვითარების პირობებში

The development of digital technologies has a great impact on traditional channels for providing banking services. The speed of introduction of innovative products and services, technological changes require great flexibility from banking regulators. Also, the active participation of the government in the development of digital technologies is one of the main factors of successful digitalization. In modern conditions, in order to ensure the development of innovation in the banking sector, new mechanisms and instruments for regulating innovative financial technologies, products and services are being created. The article specifies that the effective, safe operation and development of the digital financial space requires coordinated actions from all its participants, as well as the establishment of requirements for the assessment and monitoring of potential risks caused by innovations, timely improvement and refinement of regulatory requirements. This allows to maintain the stability of the financial system and protect the rights of consumers, and to promote the development and introduction of innovative financial products and services.

Crimes in the Banking Sector in The Laws of Vietnam and Some Countries Around the World

Digital transformation has caused the banking industry today to face the challenges of newly arising crimes. In addition to traditional crimes like before, forms of electronic banking fraud or using high technology to commit crimes tend to increase. Because technological changes and developments have caused the banking system to fail to keep up with this development and are also the cause of this crime. The laws of Vietnam and other countries have also built a legal corridor to protect and prevent violations of the banking sector. This article studies the provisions of Vietnam's criminal law in comparison and evaluation with the laws of some countries around the world. The article also concludes that Vietnam needs to find effective tools to prevent crimes in the banking sector, especially international cooperation to help banks overcome challenges and create profits, competitive position, proactive adaptation, and sustainable development.

TRANSFORMASI PENDIDIKAN PESANTREN DI ERA MODERN : ANTARA TRADISI DAN INOVASI

The transformation of Islamic boarding school education in Indonesia in the modern era is a complex phenomenon involving tradition and innovation. Islamic boarding schools, as traditional Islamic educational institutions, have the challenge of adapting to rapid developments. This is due to efforts to maintain traditional values ​​while integrating innovation values ​​as the essence of this transformation. This research aims to explain the transformation of Islamic boarding school education, describing the role of tradition and innovation, as well as the challenges and opportunities in aligning these two transformation paradigms. Researchers used qualitative research, with literature study and field study research techniques. The research results show that the transformation of Islamic boarding school education requires a balance between maintaining traditional identity and adopting innovative values, which are related to current educational needs. Education stakeholders must have knowledge about educational transformation, especially when they want to design Islamic boarding school education strategies that are responsive to social, cultural and technological changes.

Trade network dynamics in a globalized environment and on the edge of crises

At the edges of crises, the roles of trade networks and supply chains are evident. Global trade networks aggregate all legal trade activities. Thus, researchers believe that network structure changes reflect phenomena such as crises, globalization, deglobalization, or even technological development, including those related to green technologies. Although trade network analysis has been widely researched, researchers have focused mainly on one or a few products or product groups. While the impact of crises and technological changes in the case of individual products has been demonstrated in some studies, less attention has been given to structural pattern changes in trade on these products. To understand how a shock, crisis, or technological change in one product may affect the trade network of another product, the patterns and relationships of node- and network-level indicators across products need to be identified. In this study, the dynamics and interdependencies of trade networks are analyzed using a combination of network indicators, cluster analysis and causality analysis. Variations and implications of the temporal patterns and causal relationships of trade network indicators are revealed for different products and product groups. Researchers have argued that the deterioration of structural indicators exacerbates crises and amplifies their consequences. A causality analysis shows that disruptions in one product’s supply chain quickly affect the trade of other products, altering the structural characteristics of trade networks. The proposed temporal pattern analysis shows that while the 2008 financial crisis did not cause structural changes in the product trade network, indicators improved before, during, and after the crisis. Nevertheless, before the pandemic, there was a noticeable deterioration in almost all structural indicators, signaling more deglobalization. This study contributes to a comprehensive understanding of trade networks, equipping decision-makers with the knowledge to promote the resilience and sustainability of these networks in an evolving global landscape.

The effects of artificial intelligence on human resource activities and the roles of the human resource triad: opportunities and challenges.

This study analyzes the existing academic literature to identify the effects of artificial intelligence (AI) on human resource (HR) activities, highlighting both opportunities and associated challenges, and on the roles of employees, line managers, and HR professionals, collectively referred to as the HR triad. We employed the scoping review method to capture and synthesize relevant academic literature in the AI-human resource management (HRM) field, examining 27 years of research (43 peer-reviewed articles are included). Based on the results, we propose an integrative framework that outlines the five primary effects of AI on HR activities: task automation, optimized HR data use, augmentation of human capabilities, work context redesign, and transformation of the social and relational aspects of work. We also detail the opportunities and challenges associated with each of these effects and the changes in the roles of the HR triad. This research contributes to the ongoing debate on AI-augmented HRM by discussing the theoretical contributions and managerial implications of our findings, along with avenues for future research. By considering the most recent studies on the topic, this scoping review sheds light on the effects of AI on the roles of the HR triad, enabling these key stakeholders to better prepare for this technological change. The findings can inform future academic research, organizations using or considering the application of AI in HRM, and policymakers. This is particularly timely, given the growing adoption of AI in HRM activities.

The General Theory of Scientific Variability for Technological Evolution

The proposed general theory of scientific variability for technological evolution explains one of the drivers of technological change for economic progress in human society. Variability is the predisposition of the elements in systems to assume different values over time and space. In biology, the variability is basic to explaining differences and development in organisms. In economics of technical change, the effects of variability within research fields on evolutionary dynamics of related technologies are unknown. In a broad analogy with the principles of biology, suggested theoretical framework here can clarify a basic driver of technological evolution: the variability within research fields can explain the dynamics of scientific development and technological evolution. The study sees whether statistical evidence supports the hypothesis that the rate of growth of scientific and technological fields can be explained by the level of variability within scientific fields. The validation is based on emerging research fields in quantum technologies: quantum imaging, quantum meteorology, quantum sensing, and quantum optics. Statistical evidence seems in general to support the hypothesis stated that the rate of growth can be explained by the level of scientific variability within research fields, measured with the relative entropy (indicating the dispersion of scientific topics in a research field underlying a specific technology). Nonparametric correlation with Spearman’s rho shows a positive coefficient of 0.80 between entropy measures and rates of growth between scientific and technological fields. The linear model of the relation between rate of growth and scientific variability reveals a coefficient of regression equal to 1.63 (R2 = 0.60). The findings here suggest a general law that variability within research fields positively drives scientific development and technological evolution. In particular, a higher variability within research fields can support a high rate of growth in scientific development and technological evolution. The proposed general theory of scientific variability is especially relevant in turbulent environments of technology-based competition to clarify a basic determinant of technological development to design strategies of technological forecasting and management of promising innovations.

The expansion of basic education during ‘deskilling’ technological change in England and Wales, c. 1780–1830

AbstractThe first country to industrialize – England – ostensibly did so without expanding investment in the basic education of its workforce. The empirical evidence underpinning this argument for England rests largely on signature rates at marriage. These are not a perfect indication of educational achievement, particularly as many children never learned to write. More problematically, I argue signatures are likely to have systematically underestimated human capital in industrial districts. In place of signature data, I propose age heaping, a measure widely understood as a proxy for numeracy but shown here to be closely related to both reading and writing abilities. In contrast to signatures, this measure suggests that ‘deskilling’ industrialization induced human capital accumulation. I argue that this occurred not because human capital was directly productive, but rather because schools provided a valuable signal. Sunday school attendance signalled low leisure‐preference among child workers and were popularly attended in industrial districts. Further, such schools taught children to read but not write, which they considered inappropriate for the Sabbath, accounting for the discrepancy between these two measures of human capital.

The 1973 Oil Crisis: a Look after half a Century

The article examines the prerequisites and consequences of the global oil crisis of 1973. It analyzes not only the political reasons that prompted the Arab oil exporting countries to use the “oil weapon” (the unresolved Middle East conflict and the Palestinian problem), but also the crisis phenomena in the Western economy. Not only Arab countries, but also powerful oil companies, backed by Western countries, especially the United States, were interested in change. For the West, the oil crisis caused difficulties and problems in the short term, but in the long term it turned out to be a catalyst that accelerated structural and technological changes in the Western economy and in the global financial system. The oil crisis allowed the oil-producing countries of the Arab East to sharply increase the level of state income, which opened up opportunities for accelerated socio-economic development, and also increased the authority of these countries and OPEC in international relations.

Understanding the Future Competitive Advantages of the Construction Industry

Technological changes (such as Construction 4.0) in an organization cause the workforce to exhibit resistance to change, job redundancy, etc. Geographical location will no longer provide a competitive advantage, but resources will be the source of competitive advantage in the future, and these resources will be intangible, valuable, and not be easily imitated. The aim of this study is to provide an understanding of the future competitive advantages of organizations in the construction industry that could help the construction workforce easily adapt to technological changes. This study is based on resource-based theory and the ADKAR change management model. This study developed an ADREKA sequence for organizations to achieve future competitive advantage during technological changes in the construction industry. Hence, building social, relational, and human capital is necessary during technological changes to achieve competitive advantage for an organization and foster workforce adaptability to change.

An evaluation of the regional heterogeneity of museums' operational efficiency and productivity changes across Chinese provinces

Museums are critical in safeguarding cultural heritage and cultivating community educational opportunities. This research aims to evaluate operational efficiency (OE), the impact of technological change on total factor productivity change (TFPC), and the regional heterogeneity of museum performance in three regions and 31 provinces across China. To this end, the study employed DEA-SBM and the Malmquist Productivity Index to gauge OE, TFPC, and determinants of TFPC (efficiency change or emerging technologies change) across 31 provinces for 2012–2021. Results reveal that the average OE of the Chinese Museum is 0.8394. It shows a 16.06 % growth potential in the operational efficiency of Chinese Museums. Further, the OE of Chinese Museums declined over the study period from 0.8965 in 2012 to 0.8088 in 2021. Beijing, Fujian, and Hunan are ranked top with a Museum's OE Score of 1. The average MI score of Chinese Museums is 0.9744, and technology change is the main determinant of Decline in productivity change as EC = 0.9992 is greater than TC = 0.9846. The MI of Liaoning, Shanghai, Ningxia, Jiangxi, Chongqing, Sichuan, Guangdong, and Tianjin is over 1, indicating growth in total factor productivity over the study period. The eastern region of China shows higher operational efficiency and total factor productivity scores of museums than the central and western regions. The results of the Kruskal-Wallis test proved that a statistically significant difference exists among different regions of China for the OE, MI, EC, and TC of museums.

Interests of the future: An integrative review and research agenda for an automated world of work

Research on automation and the future of work is a major focus for both academics and practitioners due to technological changes disrupting the labor market and educational pathways. Although recent articles have published projections about the types of tasks and jobs most likely to be automated in the coming years, little attention has been devoted to how different types of vocational interests are susceptible to automation, as well as resulting changes to the match between people's interests and their jobs. In the present article, we provide an integrative review of vocational interests and automation projections within and across jobs. By standardizing and mapping projections to Holland's RIASEC interest model, we found that Investigative (scientific) and Conventional (detail-oriented) interests, including STEM interests, are most susceptible to automation, whereas Social (people-oriented) and Realistic (hands-on) interests are least susceptible. For Artistic and Enterprising interests, some creative work, decision-making, and leadership skills may be affected by automation across a range of jobs. We build on these projections to propose a future research agenda integrating interests, technology, and careers. Specifically, we identify five areas for future research, including using intentional work design to enhance interests, the role of interests in career decisions related to project-based work, changes in people's interests following automation, increased use of basic interests, and the systematic impacts of automation on different groups of people. Overall, this review highlights how vocational interests will remain an important topic with high relevance for career guidance, education, and organizations as the future of work evolves.