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Taiwan serves as a case study to investigate the association between the expansion and reform of higher education and the growth of science production. More specifically, what driving forces facilitated the growth of science production in different types of Taiwanese universities and other sectors, from 1980 to 2011.

The contribution charts differential contributions to overall production. Taiwanese data from Thomson Reuters’ Science Citation Index Expanded (SCIE) is analyzed to show the expansion of the higher education system and its relationship to the production of science. The author uses sociological organization theories to facilitate our understanding of how and why the landscape of science production changed.

Results show that the growth of science production is associated with processes of isomorphism and competition within the higher education system. Findings also suggest that universities quickly seized upon external opportunities and turned themselves into what is known as the “knowledge conglomerate.” Unique organizational features bolster universities’ position as the driving force behind advancing national innovation.

This study extends previous research by examining multiple sectors of higher education, using longitudinal and recent data, and highlighting themes that have been ignored or overlooked, such as competition and collaboration among universities and industry partners.

The purpose of this paper is to evaluate design performance of 51 gear shaping machines by using data envelopment analysis (DEA).

Existing studies extend traditional DEA by handling bounded and discrete data based on envelopment models. However, value judgment is usually neglected and fail to be incorporated in these envelopment models. In many cases, there is a need for prior preferences. Using existing DEA approaches as a backdrop, the current paper presents a methodology for incorporating assurance region (AR) restrictions into DEA with bounded and discrete data, i.e. the assurance region bounded discrete (AR-BD) DEA model. Then, the AR-BD DEA model is combined with a context-dependent DEA to obtain an efficiency stratification.

The authors examine different AR restrictions and calculate efficiency scores of five scenarios of AR restrictions by using the proposed AR-BD DEA model. It shows that AR restrictions have a great impact on the efficiency scores. The authors also identify nine efficient frontiers in total. For each decision-making unit, it could set benchmarks and improve its performance based on each higher efficient frontier.

This paper first evaluates efficiency of gear shaping machines by considering different (bounded and discrete) variable types of data and including AR restrictions. The AR-BD DEA model and context-dependent AR-BD DEA model proposed in this paper further enrich the DEA theory. The findings in this paper certainly provide useful information for both producers and consumers to make smart decisions.

This chapter provides an overview of the findings and chapters of a thematic volume in the International Perspectives on Education and Society (IPES) series. It describes the common dataset and methods used by an international research team.

The chapter synthesizes the results of a series of country-level case studies and cross-national and regional comparisons on the growth of scientific research from 1900 until 2011. Additionally, the chapter provides a quantitative analysis of global trends in scientific, peer-reviewed publishing over the same period.

The introduction identifies common themes that emerged across the case studies examined in-depth during the multi-year research project Science Productivity, Higher Education, Research and Development and the Knowledge Society (SPHERE). First, universities have long been and are increasingly the primary organizations in science production around the globe. Second, the chapters describe in-country and cross-country patterns of competition and collaboration in scientific publications. Third, the chapters describe the national policy environments and institutionalized organizational forms that foster scientific research.

The introduction reviews selected findings and limitations of previous bibliometric studies and explains that the chapters in the volume address these limitations by applying neo-institutional theoretical frameworks to analyze bibliometric data over an extensive period.

This paper aims to comprehensively clarify the research status of thermal transport of supercritical aviation kerosene, with particular interests in the effect of cracking on heat transfer.

A brief review of current research on supercritical aviation kerosene is presented in views of the surrogate model of hydrocarbon fuels, chemical cracking mechanism of hydrocarbon fuels, thermo-physical properties of hydrocarbon fuels, turbulence models, flow characteristics and thermal performances, which indicates that more efforts need to be directed into these topics. Therefore, supercritical thermal transport of n-decane is then computationally investigated in the condition of thermal pyrolysis, while the ASPEN HYSYS gives the properties of n-decane and pyrolysis products. In addition, the one-step chemical cracking mechanism and SST k-ω turbulence model are applied with relatively high precision.

The existing surrogate models of aviation kerosene are limited to a specific scope of application and their thermo-physical properties deviate from the experimental data. The turbulence models used to implement numerical simulation should be studied to further improve the prediction accuracy. The thermal-induced acceleration is driven by the drastic density change, which is caused by the production of small molecules. The wall temperature of the combustion chamber can be effectively reduced by this behavior, i.e. the phenomenon of heat transfer deterioration can be attenuated or suppressed by thermal pyrolysis.

The issues in numerical studies of supercritical aviation kerosene are clearly revealed, and the conjugation mechanism between thermal pyrolysis and convective heat transfer is initially presented.

Growth in scientific production and productivity over the 20th century resulted significantly from three major countries in European science – France, Germany, and the United Kingdom. Charting the development of universities and research institutes that bolster Europe’s key position in global science, we uncover both stable and dynamic patterns of productivity in the fields of STEM, including health, over the 20th century. Ongoing internationalization of higher education and science has been accompanied by increasing competition and collaboration. Despite policy goals to foster innovation and expand research capacity, policies cannot fully account for the differential growth of scientific productivity we chart from 1975 to 2010.

Our sociological neo-institutional framework facilitates explanation of differences in institutional settings, organizational forms, and organizations that produce the most European research. We measure growth of published peer-reviewed articles indexed in Thomson Reuters’ Science Citation Index Expanded (SCIE).

Organizational forms vary in their contributions, with universities accounting for nearly half but rising in France; ultrastable in Germany at four-fifths, and growing at around two-thirds in the United Kingdom. Differing institutionalization pathways created the conditions necessary for continuous, but varying growth in scientific production and productivity in the European center of global science. The research university is key in all three countries, and we identify organizations leading in research output.

Few studies explicitly compare across time, space, and different levels of analysis. We show how important European science has been to overall global science production and productivity. In-depth comparisons, especially the organizational fields and forms in which science is produced, are crucial if policy is to support research and development.

This chapter explores the trajectories of higher education expansion and its political and social conditions in seven countries, namely China, Japan, Germany, Qatar, South Korea, Taiwan, and the United States of America.

The analysis relies on longitudinal and cross-sectional data gleaned from the World Higher Education Database, UNESCO, and the OECD.

The countries have seen remarkable higher education expansion in the 20th century in terms of enrollments and the foundings of universities, with particularly strong growth in the immediate post-WWII period and since 1990. For the particular case of STEM fields (science, technology, engineering, mathematics), the chapter shows that in those higher education systems in which growth took off relatively late, universities oriented toward the STEM fields are more dominant than in those with a longer history. Countries with a more recent HE system stress technological development more than those that look back on multiple centuries of HE expansion with their canonical legacies.

Comparing these highly dissimilar countries nevertheless reveals important common patterns, and the variable paces of higher education expansion can be explained by national, social, and political factors driving the institutionalization of higher education and research.

During the 20th century, the United States rapidly developed its research capacity by fostering a broad base of institutions of higher education led by a small core of highly productive research universities. By the latter half of the century, scientists in a greatly expanded number of universities across the United States published the largest annual number of scholarly publications in STEM+ fields from one nation. This expansion was not a product of some science and higher education centralized plan, rather it flowed from the rise of mass tertiary education in this nation. Despite this unprecedented productivity, some scholars suggested that universities would cease to lead American scientific research. This chapter investigates the ways that the United States’ system of higher education underpinned American science into the 21st century.

The authors present a historical and sociological case study of the development of the United States’ system of higher education and its associated research capacity. The historical and sociological context informs our analysis of data from the SPHERE team dataset, which was compiled from the Thomson Reuters’ Science Citation Index Expanded (SCIE) database.

We argue that American research capacity is a function of the United States’ broad base of thousands of public and broadly accessible institutions of higher education plus its smaller, elite sector of “super” research universities; and that the former serve to culturally support the later. Unlike previous research, we find that American higher education is not decreasing its contributions to the nation’s production of STEM+ scholarship.

The chapter provides empirical analyses, which support previous sociological theory about mass higher education and super research universities.

This article aims to elaborate on the current relevant policies, research literature and technical applications of administrative intelligent decision-making in major countries in the world, to summarize the current focus areas of international competition in administrative intelligent decision-making and to provide references and insights for other countries.

The knowledge graph tool CiteSpace was used to conduct a quantitative analysis of the field of administrative intelligent decision-making, using the two dimensions of research literature and technology patents to analyze the basic status and evolution process of artificial intelligence applied to administrative decision-making.

Over the past 30 years, theoretical research on administrative intelligent decision-making has primarily centered on countries like the United States of America, China and Japan. The main themes include leveraging artificial intelligence (AI) technology to enable digital government transformation, enhance administrative efficiency and promote public value through service-oriented initiatives. Countries like South Korea, China and the United States of America have demonstrated significant advantages in technology development and patent applications, focusing on e-government systems, intelligent government auditing, addressing policy mismatches between supply and demand and integrating online and offline administrative services. The international competitive landscape in this field is shaped by three key factors: foundational theories, technological advancements and practical scenario applications.

Despite the rapid advancements in AI technology and the acceleration of enterprise digital transformation, discussions on the intelligent transformation of administrative decision-making leveraging next-generation information technology remain limited. This study summarizes the development trajectory of administrative intelligent decision-making in major countries worldwide, analyzes the international competitive landscape of its theoretical and application research and highlights key focus areas. These findings offer valuable insights for advancing the construction of administrative intelligent decision-making systems in other nations.

This paper aims to investigate the influence of moral disengagement, perceived penalty, negative experiences and turnover intention on the intention to violate the established security rules.

The method used involves two stages of analysis, using techniques of structural equation modeling and artificial intelligence with neural networks, based on information collected from 318 workers of organizational information systems.

The model provides a reasonable prediction regarding the intention to violate information security policies (ISP). The results revealed that the relationships of moral disengagement and perceived penalty significantly influence such an intention.

This research presents a multi-analytical approach that expands the robustness of the results by the complementarity of each analysis technique. In addition, it offers scientific evidence of the factors that reinforce the cognitive processes that involve workers’ decision-making in security breaches.

The practical recommendation is to improve organizational communication to mitigate information security vulnerabilities in several ways, namely, training actions that simulate daily work routines; exposing the consequences of policy violations; disseminating internal newsletters with examples of inappropriate behavior.

Results indicate that information security does not depend on the employees’ commitment to the organization; system vulnerabilities can be explored even by employees committed to the companies.

The study expands the knowledge about the individual factors that make information security in companies vulnerable, one of the few in the literature which aims to offer an in-depth perspective on which individual antecedent factors affect the violation of ISP.