Technology Initiative Research Articles

Analysis of Enterprise Internet of Things Maturity Models: A Review

Maturity models are valuable tools when assessing the readiness and progress of technology incorporation in organizations, providing information for decision-making, resource allocation, and competitive advantage. The Internet of Things is a technology paradigm of global importance, especially for organizations, as it supports productivity improvements, real-time analysis, and customer satisfaction. Therefore, adopting and implementing this technology in enterprises brings several challenges, such as technological, organizational, security, and maturity issues. However, secondary studies that systematically compile the existing literature on these specific mechanisms for the enterprise domain are still being determined. This article aims to address this knowledge gap by conducting a review to deepen and synthesize the existing knowledge. This research followed established methodologies and protocols to synthesize and analyze the state of the art in the area; 489 documents were retrieved from seven bibliographic databases, and, applying inclusion and exclusion criteria, 36 primary studies were selected. The results indicate that the typical structures of maturity models incorporate technological, organizational, human, performance, and security dimensions through graded levels that denote the sophistication of the Internet of Things. Measurement techniques and metrics vary from model to model. There are few empirical validations or standardized improvement frameworks. The main conclusion is that there is a diversity of models, dimensions, indicators, and methods and a need for more comprehensive, adaptable, and user-friendly tools to help companies assess their Internet of Things maturity and inform future development strategies.

Bearing fault diagnosis by sparse frequency spiral spectrum driven NAF-LDM under strong noise and small samples

Abstract The complexity of background noise and the scarcity of real fault samples seriously affect the diagnostic accuracy of the model. To address this, a noise-robust two-dimensional feature map, the sparse frequency spiral spectrum (SFSM), based on sparse representation theory, is proposed. A bridge penalty coefficient is applied to the sparse representation model to accurately select impact components, and the fast iterative shrinkage threshold algorithm is used to solve for sparse representation coefficients. Sparse reconstructed signals are obtained by convolving the impact patterns with these coefficients, leading to a sparse reconstruction algorithm with reduced computational complexity. Furthermore, the novel non-linear activation-free blocks (NAF Blocks) are embedded into the latent diffusion model to augment small samples, significantly improving image generation speed and quality. The integration of the Swin transformer for feature extraction and classification further enhances diagnostic performance. The superiority of this method is validated on the XJTU-SY dataset, a bearing experimental platform dataset, and enterprise engineering dataset. Experimental results demonstrate that the structural and generalization advantages of NAF Blocks are crucial for improving image quality and inference speed. The noise suppression capability of the proposed method, facilitated by the SFSM feature processing technique, is confirmed through ablation and noise robustness tests. Finally, the Swin transformer’s excellent feature extraction and classification capabilities for SFSM are verified. The proposed method achieves diagnostic accuracies of 99.10% and 98.7% on the XJTU-SY and experimental platform datasets, respectively.

Mapping of FinTech Ecosystem to Sustainable Development Goals (SDGs): Saudi Arabia’s Landscape

Financial technology (FinTech) has become an indispensable part of most of the business infrastructure around the world. The FinTech ecosystem provides this solution by providing a suitable environment for all financial techno services to synergize. This paper explores the relationship between FinTech programs in Saudi Arabia and the Sustainable Development Goals (SDGs). It highlights how these financial technology initiatives contribute to various SDGs by providing innovative solutions that enhance financial inclusion, improve access to essential services, and foster economic growth. Specifically, the study identifies connections between FinTech programs and SDG goals 1 (No Poverty), 2 (Zero Hunger), 5 (Gender Equality), 8 (Decent Work and Economic Growth), and 17 (Partnerships for the Goals). Through these linkages, this paper demonstrates the role of FinTech in promoting sustainable development and supporting national and global efforts to achieve these crucial objectives. Secondary data were collected from published reports, institutional and governmental websites, official portals, and research papers focusing on the companies operating in Saudi Arabia. It was found that FinTech in Saudi Arabia is addressing SDGs goals 1, 2, 5, 8 and 17. This paper further endeavors to map specific SDG indicators to the products and services provided by FinTech companies in Saudi Arabia. By doing so, it seeks to identify the areas where these technological solutions directly support the achievement of sustainable development targets. This comprehensive analysis is intended to be a valuable resource for institutions and policymakers in the FinTech industry. It provides insights into how these companies can align their offerings more closely with the SDG framework, thereby addressing any existing gaps. The findings aim to aid in the global agenda of eradicating poverty and promoting sustainable development opportunities by leveraging FinTech innovations.

Identify high-risk DOR women ≤ 35 years old following assisted reproduction technology through cutoffs of anti-mullerian hormone and antral follicle counts

BackgroundFemales with diminished ovarian reserve (DOR) have significantly lower cumulative live birth rates (CLBRs) than females with normal ovarian reserve. A subset of young infertile patients, whose ovarian reserve is declining but has not yet met the POSEIDON criteria for DOR, has not received the attention it merited. These individuals have not been identified in a timely manner prior to the initiation of assisted reproductive technology (ART), leading to suboptimal clinical pregnancy outcomes. We categorized this overlooked cohort as the “high-risk DOR” group.ObjectiveThe primary aim of this study was to identify high-risk DOR patients through anti-Mullerian hormone (AMH) and antral follicle counts (AFCs).MethodsA total of 10037 young women (≤ 35 years old) who underwent their first initial oocyte aspiration cycle at a single reproductive medicine center were included and further classified into three groups, based on the thresholds for AMH and AFC established through receiver operating characteristic (ROC) analysis and in alignment with the POSEIDON criteria. Two ROC analyses were performed to identify the cutoff values of AMH and AFC to obtain one viable embryo (one top-quality embryo or one viable blastocyst). The cutoffs of ROC were measured by sensitivity and specificity. The primary outcome was the cumulative live birth rate (CLBR) per oocyte aspiration cycle. The secondary outcomes included the number of oocytes retrieved and the number of viable embryos formed. Pearson’s chi-square tests were conducted to compare the clinical outcomes among the three groups. Furthermore, univariate logistic regression analyses were performed to investigate the associations between ovarian reserve and clinical outcomes. All of the above comparisons between the high-risk DOR and NOR were further confirmed by propensity score matching (PSM) (1:1 nearest-neighbor matching, with a caliper width of 0.02).ResultsAccording to the ROC analyses and POSEIDON criteria, the present study identified a population of high-risk DOR patients (1.20 ng/mL < AMH values < 2.50 ng/mL, with 6 ≤ AFC ≤ 10; n = 682), and their outcomes were further compared to those of DOR patients (positive control, AMH values ≤ 1.2 ng/mL, and/or AFC ≤ 5; n = 1153) and of NOR patients (negative control, 2.5 ng/mL ≤ AMH values ≤ 5.5 ng/mL, and 11 ≤ AFC ≤ 20; n = 2649). Patients in the high-risk DOR group had significantly lower CLBRs than those in the NOR group (p < 0.001) but higher CLBRs than those in the DOR group (p < 0.001). Logistic regression further demonstrated that high-risk DOR was associated with a lower likelihood of cumulative live birth chance (OR 0.401, 95% CI: 0.332–0.486, p < 0.001) than NOR was, with a greater likelihood of cumulative live birth chance (OR 1.911, 95% CI:1.558–2.344, p < 0.001) than DOR was. To investigate the effects of embryo development stage, the outcomes of D3 embryos and blastocysts were analyzed separately. Significant differences in pregnancy outcomes were detected only in D3 embryo ET cycles among the three groups (high-risk DOR vs. NOR, all p < 0.05; DOR vs. NOR, all p < 0.05). DOR/high-risk DOR did not influence the pregnancy loss rates or pregnancy outcomes (clinical pregnancy rates and ongoing pregnancy rates) per positive HCG cycle (all p > 0.05). After PSM, the differences in ovarian response and pregnancy outcomes between the high-risk DOR and NOR groups were consistent with the results before PSM.Conclusion(s)Our study revealed that the CLBR of the high-risk DOR patients was significantly lower than that of females with normal ovarian reserve and greater than that of females with DOR. The values of AMH ranging from 1.2 to 2.5 and AFC ranging from 6 to 10 appeared to constitute meaningful thresholds in females with mildly reduced ovarian reserve.

Empirical Analysis of the ESG and Financial Performance: Evidence from Chinese Technology Enterprises

To date, the concept of sustainable development has gained global attention from companies and investors. One important reason for this is the increasing interest of investors in incorporating environmental, social, and governance (ESG) elements into their investments. The purpose of this dissertation is to analyze the correlation between ESG factor performance and corporate financial performance in Chinese technology enterprises. Additionally, the study focuses on Internet and medical technology companies to ensure relevance. The findings of the study provide guidance on ESG investment and sustainability for both companies and individual investors.

Policies, Progress, and Prospects for Internet Telemedicine in China

ABSTRACT Around the world, the adoption of digital technologies in health care has accelerated considerably in the wake of the COVID-19 pandemic. Prior to the emergence of the pandemic, China had already embarked on a private sector, technology enterprise-led creation of an innovative internet health care ecosystem, which has dramatically transformed China’s health care landscape. In this article, we describe the evolution of China’s internet health market, focusing on internet telemedicine. We trace its early origins with the establishment of information networks in the 1980s, to the emergence of a fast-growing internet health market in the 2010s that leveraged the capabilities of technology enterprises in e-commerce, logistics, and payment systems. Private health care platforms have played a central role throughout this transformative process. The supplyside of the market has a unique public-private mix structure, with the coexistence of public and private internet hospitals, and with the majority of telemedicine services provided by public hospital doctors working on private platforms in a dual practice capacity. We conclude with a discussion of the prospects of internet telemedicine, including how it should be optimized and harnessed to improve China’s health system. Finally, we set out areas where more research is needed.

Cities of Vanadium: Technological Development and Post-Industrial Transformation in Emalahleni, Nizhny Tagil, and Panzhihua

The paper investigates the trajectories of social and economic development of second-tier single-industry cities specializing in metallurgy of vanadium under the circumstances of post-industrial economy. In the middle of 20th century, a technology of processing titaniferous ore made it possible to use vast deposits of previously unexploited natural resources to produce steel and vanadium. The large integrated steel mills were erected in Witbank (Emalahleni) in South Africa, Nizhny Tagil in Russia, and Panzhihua in China. Being industrial monotowns dependent on mining and metallurgy, these cities were seeking for diversification which could provide sustainable development. Such diversification was generally following two directions: either establishment of belt of smaller technological enterprises and creating section of product with higher added value, or growing the system of industries of culture, leisure, and health. While Emalahleni failed in striving for diversification due to boom in coal industry, which ultimately led to bankruptcy of its steel industry, Nizhny Tagil and Panzhihua remained successful steel-making centers even in 21st century. However, even economic success and focused attempts to diversity city’s economy by means of creative reindustrialization were circumscribed by the cultural and environmental issues caused by the very fact of such industrial survival.

Influencing Factors and Formation Mechanism of Carbon Emission Rights Prices in Shanghai, China

With the intensification of global climate change issues and increasingly stringent carbon emission controls, carbon emissions trading has become a crucial market-based mechanism for reducing carbon emissions. A deeper understanding of the factors influencing carbon emission rights prices and their formation mechanisms can enhance market transparency and effectiveness and promote the healthy development of the carbon trading market. This paper identifies the main factors affecting carbon emission rights prices and explores their formation mechanisms from both the internal and external perspectives of enterprises. Using a vector autoregression (VAR) model, it quantifies the impacts of energy prices, the climate, and technology levels on carbon trading prices in Shanghai, China. The results show that, in the short term, enterprise technology levels and energy prices significantly impact carbon emission rights prices, while the climate becomes more critical in the medium to long term. These findings propose specific policy recommendations for improving the carbon emissions trading market, with a focus on these three factors.

Posthumanist Technologies in Business: AI and Cloud Computing for Global Optimization and Ethical Challenges

. This study explores the integration of artificial intelligence (AI) and cloud computing within posthumanist technologies, focusing on their impact on business optimization and information security. A systematic review of 40 studies across sectors such as banking and retail highlights the benefits of AI in automating tasks and enhancing decision-making, while cloud computing provides flexibility and scalability. However, risks like data privacy issues, algorithmic bias, and cybersecurity vulnerabilities demand attention. The research emphasizes the need for ethical frameworks and security strategies to mitigate these risks. Additionally, it stresses the importance of equitable access to these technologies for small and medium-sized enterprises (SMEs) and marginalized communities. The study provides actionable recommendations for businesses and calls for future research on the long-term societal implications of these technologies

Innovative Service Model of Science and Technology Finance in China

This investigation analyses the financial dependence of the transformation of scientific and technological achievements, the effective connection between scientific and technological resources and financial resources, the development of emerging industries, the upgrade of technological levels and the optimization of industrial structures, and the financial support required for technological innovation and R&amp;D of high-tech enterprises as well as small and medium-sized technological enterprises. It is pointed out that the improvement of financial products, the innovation of capital markets and the application of internet finance are the operational basis of the innovation service mode of science and technology finance. Correspondingly, the upper level design at the policy level provides the basis for the development of the appropriate service model of technological and financial innovation.

Immersive Virtual Reality (IVR) Systems for Comprehensive Fire Safety Education in Primary School

In the evolving landscape of educational technology, immersive virtual reality (IVR) has emerged as a promising tool to enhance safety education for primary school students. Traditional fire safety methods, while foundational, face challenges in engaging young learners actively. This study aims to comprehensively investigate the intricate dynamics of integrating IVR technology into fire safety education for primary school students. By examining students' perceptions, assessing engagement levels, and evaluating learning outcomes, the research seeks to offer nuanced insights into the potential benefits and challenges associated with VR-based safety education. Conducted as a qualitative study, 25 semi-structured interviews were performed with primary school students (Grades 4-6 in China), employing a three-step thematic analysis. The research explores students' experiences with IVR fire safety simulations, comparing them with traditional methods, and addressing practical considerations for integration. Preliminary findings suggest positive perceptions, heightened engagement, and improved learning outcomes among students exposed to VR simulations. Practical challenges, including logistical considerations, were identified. The comparison with traditional methods illuminated strengths and weaknesses, guiding educators and policymakers. This research contributes to the intersection of education and technology by offering novel insights into the potential of IVR simulations in fire safety education. The study's significance lies in informing pedagogical practices, addressing practical challenges, and promoting safety awareness among primary school students, guiding future educational technology initiatives.

Have MSMEs in Indonesia Focused on Business Sustainability? The Influence of Environmental Orientation, Technology Implementation, Green Marketing, and Innovation Capability

The aim of this study is to determine the factors that impact MSMEs' sustainability practices and the degree to which they concentrate on business sustainability in Indonesia. This study used a quantitative research approach and collected survey data from MSMEs in Indonesia operating in various industries totaling 350 samples. Partial Least Squares Structural Equation Modeling (PLS-SEM) was used for data analysis to assess the relationship between variables. The study discovered that a focus on the environment, the application of technology, and green marketing greatly improve an organization's capacity for innovation, which in turn has a favorable impact on the sustainability of the firm. MSMEs are more likely to develop and maintain their business practices over time if they invest in green marketing techniques, use cutting-edge technologies, and give priority to environmental issues. In order to attain sustainability, MSMEs should include technology, marketing, and environmental initiatives into their fundamental business operations, according to the research. It is recommended that policymakers provide incentives, subsidies, and training programs to MSMEs in order to encourage the adoption of technology and green marketing. Support like this can encourage sustainable practices throughout the industry and close the digital divide. This study offers insightful information about the combined effects of environmental orientation, technology adoption, and green marketing on MSMEs in Indonesia's capacity for innovation and long-term viability of their businesses. It gives helpful suggestions for boosting MSMEs' sustainability and emphasizes the crucial role that innovation plays in converting these elements into sustainable business practices.

Green Supply Chain Technology Innovation and Enterprise Synergy in the Context of Sustainable Development: Challenges and Strategie

This study explores the synergistic development between technological innovation and enterprises in green logistics supply chains from the sustainable development perspective. The study first introduces the latest progress of China's environmental policies and technological innovation and analyses the importance and necessity of green logistics supply chain management. Subsequently, through case studies and theoretical research, this paper discusses the policies and regulations of green supply chain management, collaborative management among enterprises, and the development path of technological innovation. It further analyses the contents of policies and regulations, enterprise collaboration management, and technological innovation in green logistics supply chain management. It proposes strategies and suggestions to solve problems by combining cases and theories. Finally, this study summarises the development status of green logistics supply chain management. It looks forward to future development trends, emphasizing that more enterprises should strengthen cooperation to jointly promote green logistics supply chains, environmental protection, and sustainable economic and social development.

The effect of workplace bullying on knowledge sharing of the employees in scientific and technological enterprises: a moderated mediation model

PurposeThis study aims to understand how workplace bullying affects knowledge sharing among employees in Chinese scientific and technological enterprises.MethodologyA convenience sampling method was employed to survey 275 employees from scientific and technological enterprises of Yangtze River Delta, China. The survey utilized a general information questionnaire, a workplace bullying scale, an organizational belonging scale, a knowledge sharing scale, and a forbearance scale. A moderated mediation model was set up, and the hierarchical regression and the bootstrapping method were applied.FindingsThe empirical results indicated that workplace bullying has a negative effect on the knowledge sharing, and organization belonging has played mediating effect. Furthermore, Forbearance not only moderated the effect of workplace bullying on organizational belonging, but also moderated the mediated effect of organization belonging, and the effect will be stronger when employees are at a lower level of forbearance.ImplicationsThis study offers important implications for scientific and technological enterprises. The findings imply that enterprises should discourage person-related workplace bullying to increase employees’ intention to engage in knowledge-sharing behavior. Moreover, the manager of these firms should develop a culture of family so that they can care for the organization belonging.

Financial Mechanism for Sustainable Development of the Marine Economy with Respect to Technology, Digitalization, and Low Carbonization

This study explores the impact of regional financial development on the sustainable growth of the marine economy across 14 coastal cities in Guangdong Province from 2004 to 2022. To assess this, a comprehensive index system was developed to measure marine economic sustainability, incorporating key factors such as capital investment, production efficiency, and processing and trade. The findings indicate that financial development significantly enhances the sustainable growth of the marine economy. However, the interaction between financial development, technology digitalization, and low-carbon initiatives leads to diminishing returns in terms of sustainability. Through the use of the Moran index and the spatial Durbin model, the analysis reveals a dual outcome: while financial development positively influences a city’s marine economic sustainability, it exerts negative spillover effects on neighboring cities. Previous studies have primarily focused on the relationship between financial development and the marine economy at the national or provincial level, leaving a gap in understanding these dynamics at the city level. Furthermore, the coordination between financial development and marine economic sustainability across cities within the same region remains largely unexplored. This study addresses these gaps by investigating city-level dynamics and examining intercity coordination between financial development and marine economic growth. The results offer a novel perspective for policymakers, highlighting strategies to balance regional financing for the marine economy with targeted investments in science, technology, digitalization, and low-carbon initiatives. This approach seeks to optimize resource allocation and mitigate potential substitution effects. Ultimately, this research contributes to a more nuanced understanding of the complex interplay between financial development and the marine economy at both city and regional levels.

State-led smart city with Chinese characteristics: the case of Xiong’an New Area, China

ABSTRACT Smart cities have emerged as either a technical fix to challenges of urbanized accumulation or an adaptable governance strategy under neoliberal, entrepreneurial, and austerity politics worldwide. Utilizing Xiong'an New Area, the most ambitious experimentation in China, as an empirical case, we present a distinct smart city model under the governance framework of state entrepreneurialism. This paper examines the salient and proactive role of the state in the ongoing smartification and digitalization in Xiong’an New Area. We highlight the plural (geo)political agendas parallel to capital accumulation in this state project. Based on in-depth interviews and documentary analysis, we illustrate how the state steered experimental practices through innovating institutional settings and financing strategy, legitimizing ‘digital twin’ experimentation in urban management, and co-opting non-state actors, including technical professional organizations and domestic technology enterprises. Its success rests more on its demonstration effects nationwide than the ‘actually existing’ smart city/urbanism within the territory of Xiong’an. This ‘state-led smart city with Chinese Characteristics’ shows unique features of smart governance shaped by political economic dynamics in China, compared to typical smart city models in Western capitalist countries and Asian developmental countries. The findings further the nuanced understanding of smart initiatives and projects in different contexts and the role of the government through the perspective of entrepreneurialism.

LEVERAGING ENTERPRISE ARCHITECTURE FOR DIGITAL TRANSFORMATION: A STRATEGIC APPROACH TO BUSINESS AGILITY

This paper examines the critical role of Enterprise Architecture (EA) in facilitating Digital Transformation (DT) and enhancing business agility. EA serves as a comprehensive framework that aligns IT infrastructure with business processes, enabling organizations to adapt effectively to rapid technological changes and market demands. Through a detailed literature review, the paper highlights key EA frameworks, such as TOGAF and Zachman, and discusses how these frameworks support the alignment of organizational goals with technology initiatives. The analysis reveals that leveraging EA not only improves adaptability and operational efficiency but also minimizes risks associated with digital transformations. Despite the numerous benefits, challenges such as implementation costs, resistance to change, and integration complexity are acknowledged. The paper concludes by offering recommendations for businesses to optimize their EA practices for successful digital transformation and suggesting areas for future research, including the exploration of EA's impact across various industries and the role of leadership in managing digital initiatives.

Technological Progress as a Catalyst for Energy Efficiency: A Sustainable Technology Perspective

Enhancing energy efficiency through sustainable technological progress is imperative for pursuing sustainable development, particularly in developing countries where economic growth is strongly linked to higher energy consumption. In Tunisia, an open and developing economy, fossil energy consumption can be reduced without compromising economic growth by focusing on diminishing energy intensity. This study investigates the effects of technological progress on the overall energy intensity in Tunisia from 1980 to 2019, examining the role that technological advancements may play in attaining sustainable development goals. This study is based on a growth accounting model that uses time-series analysis and a cointegration estimation approach. Our empirical results suggest the presence of a long-term connection between the variables. The attainment of enhanced energy efficiency is contingent on the growth rate of technological progress, which should exceed capital and labor productivity. The results reveal that the net impact of technological advancements is estimated at -0.0163, which signifies that aggregate energy intensity tends to decrease by an annual average of 1.63% in the long term. These findings underscore the need for developing economies to restructure their energy policies and support sustainable technological initiatives and green entrepreneurship. Developing countries can reduce their energy intensity while boosting their economic growth by fostering technological innovation. This study demonstrates how technological progress and green entrepreneurship can be leveraged to enhance energy efficiency and drive sustainable development in developing nations.

A deep convolutional neural network for Blind element Error Correction of Spatial Heterodyne Spectrometer using line selective convolutional blocks

The "GF Special Project" is a massive remote sensing technology initiative including a number of satellites and various observation platforms. GF-5 is the satellite with the most payloads, the highest spectral resolution, and the most difficulty in development, and it can monitor a variety of environmental elements using spatial heterodyne spectroscopy (SHS) technology, including atmospheric aerosols, carbon dioxide, methane, terrestrial vegetation, straw burning, and urban heat islands. In this study, a novel blind element error correction technique based on deep learning network is investigated and developed for spatial heterodyne interferograms, as well as the formation mechanism and distribution characteristics of the SHS interferometric data. LSConv-Net, a new CNN model, was created and trained to denoise in the presence of high-density and ultra-high-density blind element errors. We do this by introducing a new line-selective convolutional (LSConv) block. Simultaneously, experimental validation of blind element error correction utilizing laboratory water vapor interferometric data and atmospheric CO2 absorption interferometric data from GF-5, and the change in FWHM before and after the experiment was tested using potassium lamp interferograms. Experiments show that the Deep neural networks trained with this model may successfully suppress the effect of blind element noise on spectra, recover spectra that have been overwhelmed by high-density blind element noise without any effect on other non-blind pixels, and surpass all similar techniques in terms of spectral recovery.

Empowering Malaysia’s Youth: Assessing the Impact of STEM Education

The objective of this study is to assess the effectiveness of a Science, Technology, Engineering, and Mathematics (STEM) initiative in attaining the objectives specified in Malaysia's Education Development Plan (PPPM) 2013- 2025. This study emphasises the significance of incorporating STEM education in Malaysia, with a specific focus on its contribution to the development of analytical thinking, problem-solving abilities, and creative thinking among the youth. The focus of this study is specifically directed towards the country of Malaysia. This underscores the need to employ a comprehensive and interdisciplinary methodology while developing a strategy The present study involves the analysis of replies provided by participants enrolled in a STEM education program. The dataset comprises demographic data of students spanning from Forms 1 to 5, together with information pertaining to their levels of interest in STEM. The analysis of post-program surveys indicates a notable increase in agreement and high agreement, particularly in the subjects of Mathematics and Engineering. This trend suggests an increasing level of enthusiasm among individuals toward pursuing careers in the STEM disciplines. A large majority (78%) of participants said the program influenced their future STEM interests, especially in engineering.