Technology Initiative Research Articles

Preface for the Special Issue of the Review of Socionetwork Strategies: Harnessing Social Networks, Technology, and Business Strategies for Small and Medium Enterprises (SMEs)

Preface for the Special Issue of the Review of Socionetwork Strategies: Harnessing Social Networks, Technology, and Business Strategies for Small and Medium Enterprises (SMEs)

INDIVIDUAL FACTORS, SOCIAL RELATIONS, UTILIZE SOCIAL MEDIA ON BUSINESS DEVELOPMENT

Globalization and the development of information technology, the Micro, Small and Medium Enterprises sector has become the main pillar in driving the local economy. Garut Regency, West Java, has great potential in developing MSMEs which play an important role in job creation, economic growth and income distribution. There are challenges in optimizing the growth and sustainability of MSMEs in this area. This research aims to examine the influence of individual factors, social relationships, and the ability to utilize social media on the development of MSME businesses in Garut Regency. The method used is an explanation survey with a quantitative and qualitative approach (mixed methods). Quantitative data was collected through questionnaires, while qualitative data was obtained from Focus Group Discussions and in-depth interviews. The results of analysis using Structural Equation Modeling show that individual factors have an influence of 32.1%, social relations have an influence of 32.9%, and the ability to utilize social media has an influence of 35.9% on the development of MSME businesses in Garut Regency. Simultaneously, these three factors have an influence of 44% on business development. This research provides a basis for formulating more effective policies and programs to support the growth of MSMEs in Garut Regency.

Predicting the Growth Value of Technology Enterprises with an Optimized Back-propagation Neural Network

Predicting the Growth Value of Technology Enterprises with an Optimized Back-propagation Neural Network

Digitalization of Public Finances and Public Procurement in Morocco

This article explores the impact of the digitization of public finances and the dematerialization of public procurement on the business climate in Morocco. Through empirical analysis, we demonstrate how these technological initiatives contribute to improving efficiency, transparency and economic competitiveness in a Moroccan context. Drawing on a robust methodology and data collected from a wide range of stakeholders, the study reveals a direct positive effect of dematerializing public procurement on the business climate. This process simplifies administrative procedures, reduces processing times and minimizes the risk of corruption, thereby boosting investor confidence and stimulating economic activity. While the influence of the digitization of public finances, while positive, does not appear to be statistically significant, it does include initiatives such as integrated financial management and budget transparency. These measures improve the management of public resources and reduce tax fraud, although their impact is more diffuse.

The Impact of Financial Innovation on Environmental Protection:Literature Review and Case Study

This study explores the relationship between financial innovation and environmental protection, focusing on how financial innovation can contribute to sustainable development and ecological conservation. Through a comprehensive literature review, this paper identifies various forms of financial innovation, including green finance, socially responsible investing, and impact investing. These have emerged as significant tools in promoting environmental sustainability. The literature suggests that financial innovation plays a crucial role in directing capital towards environmentally friendly projects and companies, thereby reducing the funding of polluting industries. The implementation of green bonds, green banks, and other financial instruments has been instrumental in channeling investments towards renewable energy, clean technology, and other eco-friendly initiatives. These financial mechanisms not only encourage corporate responsibility but also stimulate innovation in clean technologies by providing necessary funding and risk management solutions.The Case study is presented to exemplify the practical application of financial innovation in environmental protection. The case focuses on the development and impact of a green bond issuance by a major financial institution, highlighting the positive environmental outcomes achieved through the financing of specific sustainable projects. The analysis reveals that such financial products have led to measurable reductions in greenhouse gas emissions and improvements in resource efficiency. By synthesizing theoretical insights and empirical evidence, this research contributes to a deeper understanding of the nuanced interplay between finance and environmental preservation, suggesting that financial innovation can be a powerful ally in the global effort toward ecological conservation and sustainable development.

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.

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.

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.

SUSTAINABLE GROWTH RATE OF LISTED TELECOMMUNICATIONS TECHNOLOGY ENTERPRISES IN VIETNAM

The article clarifies the basis for discussion on sustainable growth and models for measuring sustainable growth rate. The article uses Higgins' sustainable growth model to determine the steady growth rate of the Securities Telecommunications technology enterprise in Vietnam. The results were found: Listed telecommunications technology enterprises in Vietnam had an average solid growth rate of -0.04 - 0.078, the highest solid growth rate in 2017 with a value of Quantity value 0.2189, 2021 recorded a return to growth; however, the period from late 2022 to early 2023 saw businesses in the industry gradually decreasing in growth due to weak demand. by the risks of deterioration in world economic exchange and applying detection capabilities. Despite facing complex and large-scale difficulties with benefits from policies to promote digital economic development, the business community in the industry is still able to maintain a steady growth rate and develop strongly in the near future.