Technological Capabilities Research Articles

Surface roughness reduction in electron beam powder bed fusion additive manufacturing of super duplex stainless steel 2507: investigating optimisation techniques and face orientation-dependent irregularities

AbstractThe use of additive manufacturing in metals by powder bed fusion via electron beam (PBF-EB) is increasing for fabricating high-quality parts meeting industrial standards. However, high surface roughness poses a consistent challenge in PBF-EB. This study investigates two novel approaches to optimise surface roughness for a given machine and powder combination. Using machine control software’s recently introduced research mode functionality, we develop customised beam control code to effectively explore a vast parameter space. Additionally, we explored the impact of beam travel direction and spot morphology on surface roughness. Line-melt-based contours were explored by specimen manufacturing with layer-wise parameter change, whilst spot-melting-based samples were built using a full factorial design of experiments with four factors at three levels. Initial sample characterisation was done using a stylus-based contact profilometer, followed by detailed evaluation using focus variation microscopy. Results reveal that increasing beam power and spot energy exacerbate surface roughness. We also find that a well-defined energy distribution at the spot's edge contributes to smoother surfaces. Whilst the influence of beam travel direction on surface roughness remains uncertain, our findings underscore the importance of parameter selection in achieving optimal results. By adjusting contouring parameters, we achieve a vertical roughness of Ra17.7 ± 0.9 (Sa 21.6), significantly lower than in the current literature. These findings advance our understanding of surface roughness optimisation in PBF-EB and offer practical insights for improving part quality in industrial applications. By harnessing tailored beam control strategies, manufacturers can enhance the capabilities of additive manufacturing technologies in producing metal components.

The impacts of emotional intelligence and IOT on operational efficiency in manufacturing: A cross-cultural analysis of Nigeria and the US

This review paper explores the dual impacts of Emotional Intelligence (EI) and the Internet of Things (IoT) on Operational Efficiency (OE) in the manufacturing sectors of Nigeria and the United States, providing a comprehensive cross-cultural analysis. In an era where manufacturing industries globally are undergoing rapid technological advancements and organizational transformations, understanding the synergistic role of human and technological factors is crucial. EI, which encompasses the ability to recognize, understand, and manage emotions, significantly influences leadership effectiveness, team dynamics, and overall workplace harmony. Concurrently, the integration of IoT technologies facilitates real-time data monitoring, predictive maintenance, and enhanced automation, leading to substantial improvements in OE. The paper first delineates the conceptual frameworks of EI and IoT, highlighting their individual contributions to manufacturing efficiency. Subsequently, it discusses the comparative analysis of the manufacturing environments in Nigeria and the US, examining how cultural contexts shape the application and impact of EI and IoT. In the United States, advanced technological infrastructure and a culture of innovation foster the widespread adoption of IoT and the integration of EI in organizational practices. Conversely, Nigeria's manufacturing sector, while facing challenges such as infrastructural deficits and skill gaps, shows potential for growth through targeted investments in technology and human capital development. Through this cross-cultural lens, the paper identifies key differences in the perceptions and applications of EI, the extent of IoT integration, and the resulting OEs. The findings suggest that while the US benefits from a mature ecosystem for both EI and IoT, Nigeria's unique socio-economic landscape necessitates tailored strategies to harness these tools effectively. The analysis concludes with policy and practical implications, offering insights for enhancing manufacturing efficiency through balanced and culturally sensitive approaches to technological and EI advancements. This comprehensive review underscores the importance of synergizing human and technological capabilities to drive sustainable growth and competitiveness in the global manufacturing sector. Keywords: Emotional Intelligence, Internet of Things, Operational Efficiency, Manufacturing, Cross-Cultural Analysis, Nigeria and United States.

Industrial and innovation policies in times of crisis: a widening technological divide?

Purpose The purpose of this paper is to analyze the ongoing revival of industrial and innovation policies across developed and developing economies. Design/methodology/approach The paper compare the scale and scope of recent industrial and innovation policy initiatives across developed and developing economies. Also, it analyzes recent data regarding R&D investments and other innovation indicators. Findings There are enormous disparities across economies in their capacity to implement industrial policies, particularly those to support science, technology and innovation. Most developed economies, and a few developing economies, are implementing bold, ambitious and medium-term innovation policies towards bolstering R&D investments, supporting advanced manufacturing and green energies and strengthening technological capabilities. Amid lack of fiscal policy space and vulnerable debt sustainability positions, institutional deficiencies and weak innovation ecosystems, developing economies – particularly in Africa and Latin America – face enormous challenges to implement strategic industrial and innovation policies. Research limitations/implications Under the current economic, financing and institutional conditions, together with subdued global trade and ongoing geopolitical fragmentation, the technological divide and innovation asymmetries across economies will likely widen even further, paving the ground for a “development divergence” in the coming decade. Originality/value The paper analyzes the implications of the current industrial and innovation policy trends across developed and developing countries. Under the current economic, financing and institutional conditions, together with subdued global trade and ongoing geopolitical fragmentation, the technological divide and innovation asymmetries across economies will likely widen even further, paving the ground for a “development divergence” in the coming decade.

Research on Supplier Selection of Pharmaceutical Enterprises under the Dual Carbon Target

With the proposal of national carbon peak and carbon neutrality targets, green supply chain management has become one of the important means of reducing carbon emissions. Based on elaborating on the connotation of new quality productivity, this article analyzes the supplier selection problem of pharmaceutical enterprises under the dual carbon target. A pharmaceutical supplier evaluation index system has been established from five aspects related to low-carbon and environmental protection, including technological innovation, research and development capabilities, digitization, intelligent production, environmental protection technology, and so on, with five primary indicators and 18 secondary indicators. Secondly, a game theory combination weighting method combining the G1 method and entropy weight method is used to determine the weights of indicators. A pharmaceutical supplier evaluation model is established by combining the matter element extension model. A company is used as an example to evaluate its 8 candidate suppliers and select the best supplier. Finally, corresponding measures are proposed to promote the healthy and sustainable development of pharmaceutical enterprises.

Photo-annealed electrospun TiO2 nanofibers as ion-storage layer for self-rechargeable Zn-based electrochromic energy storage device

Developing a self-rechargeable transparent electrochromic energy storage device (EESD) is highly demanding for advancing electrochromic technology and energy harvesting capabilities. In this study, we introduce a room-temperature photo-annealing method to fabricate electrospun titanium oxide (TiO2) nanofibers, serving as an ion-storage layer (ISL) on the counter electrode. By monitoring the composition and morphology of the precursor before and after ultraviolet/ozone irradiation, we confirm the formation of oxide nanostructures in electrospun TiO2 nanofibers, which enhances ion transport in the fabricated EESDs. The structural and surface properties of the photo-annealed ISL are comprehensively analyzed using various characterization techniques. Enhanced electrochromic performances are evidenced through cyclic voltammetry, spectroelectrochemical measurements, and charge storage assessments. The Zn-based EESDs with ISL (ISL Zn-EESDs) display rapid electrochemical kinetics, high charge-storing capacities, and long lifespans, with open-circuit potential of 1.2 V, optical contrast of 77 %, discharge capacity of 92 mA h/g, coloration efficiency of 58.63 cm2/C, and 99.9 % efficiency retention up to 250 cycles in both flat and bent states. Furthermore, the practical viability of the ISL Zn-EESDs is demonstrated by powering an LED lamp for several minutes. This approach highlights the potential of ISL Zn-EESDs for developing flexible smart windows, opening up a range of promising applications.

The emergence of new regional technological specialisations: exploring the role of organisations and their technological network structure

ABSTRACT Technological collaborations are crucial for shaping the emergence of new regional technological specialisations. This article explores the relationship between technological networks formed between organisations, within and across regions, and the ability of these regions to branch into new technological fields. To identify the organisations’ collaboration structure, we exploit patent co-applicant data and perform a network analysis of the organisations’ collaborations for 245 European NUTS-II regions from 1990 to 2016. Panel regression analyses reveal that (1) a more locally oriented and less dense region-internal network, (2) a more diverse set of region-external linkages, and (3) a higher share of single applicants in a region are positively associated with the emergence of new technological specialisations. These findings highlight the importance of maintaining a balance between the organisations’ inward and outward orientation to acquire new technological specialisations. Regions must leverage both internal technological capabilities and external networks to foster processes of technological renewal.

The AUKUS debate in New Zealand misses the big picture

ABSTRACT The topic of whether New Zealand should participate in AUKUS or not has emerged as a significant debate in popular political discourses in 2024. Thus far, clear pro-AUKUS and anti-AUKUS camps have developed. The pro-AUKUS camp emphasises the growing threat of China in the Indo-Pacific and New Zealand’s lacking technological capabilities that have it exposed if a conflict emerges. The anti-AUKUS camp emphasises New Zealand’s embedded independent foreign policy and staunch anti-nuclear stance which makes participating in AUKUS an ethically untenable option. However, neither side has considered the deeper, ontological questions on the table and how this affects New Zealand’s main foreign policy concern: the Pacific. New Zealand’s recent engagement with the Pacific and its experimentation with a Māori foreign policy led it to being a champion of the Blue Pacific narrative, an ontologically distinct approach that challenges the geopolitically-focussed Indo-Pacific concept. Yet, in the wake of New Zealand's flirtation with AUKUS, the Blue Pacific has been largely ignored in debates. Ultimately, the debate about AUKUS misses the big picture as it, so far, limits the focus on the true existential threat to New Zealand and the Pacific which is not China’s rise but rather climate change.

Artificial Intelligence and Technological Innovation: Evidence from China’s Strategic Emerging Industries

Artificial intelligence (AI) is the driving force for the leapfrog development of science and technology, the optimization and upgrading of industry, as well as the overall leap in productivity. Using panel data of strategic emerging firms in Chinese A-Share Listed companies from 2012 to 2022, this study empirically examines the impact of AI on technological innovation through a two-way fixed-effects model. The study discovered that technological innovation capability can be greatly enhanced by the degree of AI present in strategic emerging industry businesses. This conclusion remains valid following a series of robustness tests. The mechanism study demonstrates how the degree of AI increases businesses’ capacity for technological innovation by lowering funding constraints and boosting R&D investment. According to heterogeneity analysis, AI has varying empowering effects on different industries within strategic emerging industries. Its strongest empowering effect is observed in the western region, with the central and eastern regions seeing the weakest effects. Additionally, the promotion effect of AI is greater for state-owned enterprises than for non-state-owned enterprises. To better play the role of AI in encouraging the technical innovation of firms in strategic emerging industries, it is required to establish dedicated funds, create an AI technology innovation platform, and develop differentiated regulations.

Reading the Smoked Fish MSME Market Competition Map Through Analysis of Porter's Five Forces of Perception

Fisheries are a superior commodity and are still a favorite on the world market. Processed seafood that is quite interesting to discuss is smoked fish. The smoking activity itself provides several benefits, including: providing a preservation effect on fish meat, improving the taste of fish, and utilizing excess catches during the abundant fishing season. In the journey of Smoked Fish UMKM, of course there are various obstacles faced, including decreased turnover, lack of technological capabilities and marketing networks. Porter's Five Forces can be used to identify industry-specific competitive strategies for businesses. For Jrakahpayung smoked fish MSMEs to overcome the challenging competitive environment, competitive strategy planning is very helpful. Based on the analysis, Jrakahpayung smoked fish MSMEs are not too affected by the threats posed by business competitors because there are only a few comparable MSMEs. However, because the quality of the raw materials used must always be maintained so that consumers are loyal to Jrakahpayung smoked fish products, the threat to buyers and suppliers is quite high. On the other hand, consumer purchasing power automatically decreases if suppliers do not provide high quality raw materials. The total value of the threat of new entrants is 2.4 medium, the bargaining power of buyers is 3.5 high, the threat of substitutes is 1.9 low, the bargaining power of suppliers is 4.8 high, competition between existing competitors is 2.4 medium.

Plasma‐flash sintering: Metastable phase stabilization and evidence of ionized species

AbstractThe first demonstration of plasma‐flash sintering (PFS) is presented in this work. PFS is performed under a low‐pressure atmosphere that consecutively generates plasma and flash events. It is shown, by using several combined characterization techniques, that PFS stabilizes metastable phases on the surface of the material, which may be partially, but not solely, attributed to the generation of oxygen vacancies, and induces the absorption of ionized species, if a reactive atmosphere is employed. Even though additional research is required to understand the fundamentals of PFS, it is evidenced its potential to be used as a material surface engineering tool, which may widen the technological capabilities of flash sintering.

The "Magical Theory" of AI in Medicine: Thematic Narrative Analysis.

The discourse surrounding medical artificial intelligence (AI) often focuses on narratives that either hype the technology's potential or predict dystopian futures. AI narratives have a significant influence on the direction of research, funding, and public opinion and thus shape the future of medicine. The paper aims to offer critical reflections on AI narratives, with a specific focus on medical AI, and to raise awareness as to how people working with medical AI talk about AI and discharge their "narrative responsibility." Qualitative semistructured interviews were conducted with 41 participants from different disciplines who were exposed to medical AI in their profession. The research represents a secondary analysis of data using a thematic narrative approach. The analysis resulted in 2 main themes, each with 2 other subthemes. Stories about the AI-physician interaction depicted either a competitive or collaborative relationship. Some participants argued that AI might replace physicians, as it performs better than physicians. However, others believed that physicians should not be replaced and that AI should rather assist and support physicians. The idea of excessive technological deferral and automation bias was discussed, highlighting the risk of "losing" decisional power. The possibility that AI could relieve physicians from burnout and allow them to spend more time with patients was also considered. Finally, a few participants reported an extremely optimistic account of medical AI, while the majority criticized this type of story. The latter lamented the existence of a "magical theory" of medical AI, identified with techno-solutionist positions. Most of the participants reported a nuanced view of technology, recognizing both its benefits and challenges and avoiding polarized narratives. However, some participants did contribute to the hype surrounding medical AI, comparing it to human capabilities and depicting it as superior. Overall, the majority agreed that medical AI should assist rather than replace clinicians. The study concludes that a balanced narrative (that focuses on the technology's present capabilities and limitations) is necessary to fully realize the potential of medical AI while avoiding unrealistic expectations and hype.

Improving the Regional Science and Technology Innovation Ability under the Background of Data Element Marketization: Insights from the Yunnan Province

Under the background of the marketization of data elements, enhancing regional scientific and technological innovation capabilities has become the main driving force for urban sustainable development. It contributes to the sustainable development of the region. Based on the data of the Yunnan statistical yearbook, we built a regional science and technology innovation index system from three dimensions of science and technology innovation input, output, and benefit. Firstly, the entropy method is used to obtain the weight of each index. Secondly, TOPSIS is used to evaluate the 36 index data of each prefecture. Finally, the scores and rankings of the scientific and technological innovation ability of each prefecture are obtained. The research can effectively find the advantages and disadvantages of scientific and technological innovation in the Yunnan Province, provide data support and decision support for regional economic development, and play an important role in promoting the level of technological innovation in modern industries. At the same time, research projects can help various regions allocate various technological innovation resources reasonably, enhance their original innovation capabilities, lead the development of strategic emerging industries and future industries, and accelerate the formation of new quality productivity.

Exploring artificial intelligence (AI) chatbots adoption among research scholars using unified theory of acceptance and use of technology (UTAUT)

The use of artificial intelligence (AI) tools, such as chatbots, has significantly increased in academia and research. The present study seeks to determine the key factors influencing chatbot adoption, as well as attempts to validate the unified theory of acceptance and use of technology (UTAUT) in the context of AI chatbots adoption among research scholars. The data for this study were collected through purposive sampling using a cross-sectional survey. The population of the study comprised research scholars enrolled in three public sector universities in Pakistan. The eight-factor proposed measurement model was estimated using confirmatory factor analysis (CFA) based on 30 valid items. The goodness of fit indices suggest a favourable fit for the model χ2 = 1.710, DF = 381; p = 0.000; IFI = .902; TLI = 0.886, CFI = 0.900, RMSEA = 0.056. Our research affirms that social influence, trust, and facilitating conditions play pivotal roles as primary predictors of behavioural intentions for AI chatbots adoption among scholars. The study suggests that the perceived risks associated with using AI chatbots due to their potential misuse can be minimized by effectively implementing AI user guidelines, and developing AI literacy among scholars. Information professionals and ethical libraries can play an important role in “building the bridge” between cutting-edge technology capabilities and information users’ needs and rights. The proposed eight-factor AI chatbots adoption model holds substantial potential in understanding the influence of performance expectancy, effort expectancy, social influence, trust, perceived risk, and facilitating conditions on behavioural intention to AI chatbots adoption. This study contributes to the limited body of research investigating the factors influencing AI chatbot adoption among research scholars using the UTAUT model with additional constructs for trust and perceived risk.

Exploring the mechanism of path-creating strategy for latecomers: a combined approach of econometrics and causal machine learning

In this paper, the traditional econometrics method and causal machine-learning method are combined to study the mechanism of a path-creating strategy of latecomers to influence latecomers’ catch-up performance. A total of 283 high-tech manufacturing enterprises listed on the Shanghai and Shenzhen stock exchanges from 2007 to 2019 were selected for the study. OLS linear regression model verifies that path-creating has a positive impact on latecomers’ technological catch-up performance, technological capability plays an intermediary role between path-creating and technology catch-up performance, technological innovation appropriability positively moderates the effect of path-creating on technological capability, and technological innovation cumulativeness negatively moderates the effect of path-creating on technological catch-up but positively moderate the effect of technological capability on catch-up performance. Through machine learning, on the one hand, a conclusion basically consistent with the linear regression model is obtained, but on the other hand, a more heterogeneous situation is presented. Through analyses of the individual treatment effect of a path-creating strategy of latecomers, the Shapley value graph shows the complex influence of different features on the treatment effect of the enterprise using the path-creating strategy. Through the decision tree, some more complex patterns are found. In addition, the decision tree model based on causal analysis can also assist enterprises in making strategic decisions.

Enhancing Firm Performance: How Entrepreneurial Orientation and Information Technology Capability Interact

Applying information technology capabilities (ITC) to business processes is critical in the current data and information age. However, various bottlenecks and barriers restrict the adoption of ITC. To address these obstacles, fostering an entrepreneurial orientation (EO) can be beneficial. Drawing on the dynamic capabilities view, this study develops and tests a model that empirically analyzes how EO influences the adoption of ITC. The proposed model also assesses the separate and joint effects of EO and ITC on firm performance (FP). The research hypotheses were tested using a survey of 157 Chilean firms, and the PLS-SEM method was applied. The findings indicate that EO promotes the development of ITC and that the synergistic relationship between the two positively affects FP. These findings provide valuable insight for managers in terms of aligning their strategic approach with technological capabilities to enhance their company’s success.

Effects of Automation on Mexican Automotive Employment: 2013–2022

AbstractThis article analyses the empirical relationship between the introduction of automation technology—industrial robots—and the employment and wages of workers in the Mexican automotive industry from 2013 to 2022. Drawing on contemporary debates surrounding automation and technological unemployment, we describe the Mexican labour market’s conditions in the context of trade openness, the technological capabilities of the Mexican automotive industry, and the implementation of industrial robots. We examine this relationship using a random effects panel data model across 14 Mexican states, constructed with values from the Monthly Survey of the Manufacturing Industry (EMIM), the Mexican Ministry of Economy (SE), and the International Federation of Robotics. Our results suggest that adopting industrial robots correlates positively with the employment and salaries of automobile sector workers in the study period. We discuss the implications of changes in jobs and wages in the Mexican automotive industry, highlighting the consequences of technological change.

Online Learning from the Peers in Higher Education

The main reason for the research is to find out what factors affect the student's participation and engagement to peer learning in the university's online course. Today's higher education has a strong foothold in learning theories and pedagogical approaches that focus on collaborative learning, networking and working with peers. Now when digital technology and eLearning platforms have established their place in the infrastructure of educational institutions, we should have the keys to implementing modern education in practice. The hypothesis of the article suggests that we do not yet know how to exploit the capabilities of modern learning technology in a way that students can learn from their colleagues, peers. The practical objective of this article is to create information for planning online courses and organizing weekly tasks. The research data for this paper was drawn up from two different online implementations of the single university course. Students conducted a Moodle-based survey in which they were asked about the pedagogical approach and tools of the course. One aspect of the research is to increase the understanding of the students' opinions of peer activities in an online course. The theoretical background of the research is based on theories of active learning and learning communities. The research data are also reflected in the scientific literature on peer learning and peer assessment. According to the results, students' opinions on peer learning are quite positive. Students are able to appreciate the learning opportunities offered by assignments and activities, which are open and visible to everyone during the course. Most of the students were not interested in peer assessment, but preferred feedback and grade produced by the teacher. Most of the students opposed the small group assignments of the online course. According to the data, students feared that their contribution was considered weak in the eyes of others in the course. The results of this document underline the need for further research into peer learning in higher education. Many strategies that utilize collaborative learning may be useful, but there are still questions about the individual needs, fears and motivation of peer learning. In addition, it would be important to find a way to strengthen mutual trust through online courses.

Technological innovation, investment strategies, and innovation capabilities: Basis for small, medium enterprises competitiveness framework

Technological innovation, investment strategies, and innovation capabilities: Basis for small, medium enterprises competitiveness framework

Empirical analysis of 5G deployments: A comparative assessment of network performance with 4G

The advent of 5G networks has introduced new challenges for network operators, particularly in terms of coverage, capacity, and service quality. Consequently, it is crucial to monitor and assess network performance to detect irregularities and enhance functionality and deployment efficiency. This is especially important for Non-Standalone (NSA) 5G networks, which rely on existing 4G infrastructure and may not fully utilize the advanced capabilities of 5G technology. This study evaluates wireless system/network performance, focusing on key quality indicators and data throughput within typical town settings featuring various operational scenarios. To achieve this, portable smartphone devices were employed to simultaneously measure real-world data from all 5G and 4G networks, providing a comparative analysis across all (three) cellular network providers in the area.Results highlight differing 5G rollout strategies and performance across operators, revealing that broad coverage may struggle with congestion issues, while a tailored deployment approach could yield better results. Additionally, the analysis pinpoints performance challenges related to coverage, throughput, resource utilization, and interference, thus guiding enhancements in 5G network deployments and establishing a baseline for tracking the evolution of 5G performance.

Design Proposals for High-Voltage Stacked Configuration GaN Module

In this paper, the operational verification of the stacked transistor configuration is provided, focusing on the use of GaN transistors. The methodology is based on simulated and laboratory experiments. The stacked transistor configuration appears to be a promising solution to increase the voltage-blocking capability of GaN technology for high-voltage operations. Currently available GaN transistors are manufactured for 650 V of blocking voltage. Devices with a higher voltage-blocking capability are not currently available. Therefore, the stacked module was verified, while the main focus was on the driving circuit design, verification, and testing. For this purpose, two alternatives of GaN transistor technology have been compared. The main goal was to reach 800 V of blocking voltage with acceptable voltage deviation for nominal power of a power semiconductor converter.