Innovative Information Research Articles

Family model diabetes self-management education and support in faith-based organizations in the Republic of the Marshall Islands: A study protocol

IntroductionThe Republic of the Marshall Islands (RMI) is an independent nation and a member of the United States (US) Affiliated Pacific Islands through a Compact of Free Association. Health disparities in the RMI are striking, with high rates of type 2 diabetes mellitus (T2DM). The International Diabetes Federation has documented age-adjusted prevalence of T2DM at 23.0 %, compared to the US (13.2 %) and globally (9.8 %). T2DM has a devastating impact on patients and their families. MethodsThe purpose of this article is to present the study protocol for the fully powered two-arm cluster randomized controlled trial using a wait-list control to evaluate the effectiveness of a Family Diabetes Self-Management Education and Support (Family DSMES) program when delivered in a group setting by community health workers (CHWs) in faith-based organizations (FBOs) in the RMI. The study used a community engaged approach, and the study protocol includes adaptations based on the results of our one-arm pilot study. SummaryThis study will provide new and innovative information on the effectiveness of Family DSMES delivered in a group setting by CHWs in FBOs in the RMI. The knowledge gained from this research will inform DSMES interventions conducted with Marshallese and other Pacific Islander communities, as well as DSMES interventions conducted in other low-resource countries.

Methodological foundations of somatoscopic research in automated decision support systems

Automated Decision Support Systems (ADSS) are widely applied in various fields of science and technology, particularly in medicine, where their role in diagnostic, prognostic, and therapeutic processes is undeniable. The use of computational technologies in medical practice has become a necessary stage in the development of the field; however, the increasing volume of data that requires processing, along with heightened demands for accuracy, speed, and reliability of recommendations, significantly complicates decision-making processes. The growing amount of data, combined with the need to minimize the risks of erroneous decisions, drives the scientific community to seek innovative information technologies that can ensure a high level of accuracy in computational operations while minimizing the time required for their execution. Somatoscopic measurements, which are a crucial element in assessing the condition of the musculoskeletal system and overall physical posture of a patient, require precise and systematic image analysis that allows the identification of critically important anatomical markers. This process involves the accurate determination of key points on images of anatomical structures, which serves as the foundation for making precise predictions about the patient's condition and subsequent treatment planning. In the context of continuously increasing volumes of medical data and stricter requirements for the quality of decisions, the implementation of innovative technologies, particularly deep learning, becomes increasingly relevant as it enhances the processes of analysis and diagnosis. The aim of this study is to conduct a comprehensive analysis of the methodological aspects of applying deep learning in the context of automating the diagnosis of the musculoskeletal system and posture assessment. The study emphasizes the use of specialized neural network architectures that enable the identification of key anatomical points on images, thereby facilitating a deeper and more accurate analysis of anatomical structures. This approach significantly improves the efficiency of diagnostic processes by minimizing the likelihood of errors in decision-making and optimizing the performance of medical systems. The results of the conducted research demonstrate the significant potential of deep learning algorithms in medical systems for the automated analysis of images, allowing for substantial improvements in the accuracy and speed of decision-making. Such automation contributes to reducing the risk of subjective errors associated with the human factor, which is particularly important in complex clinical cases. Therefore, the further development of research in this direction is of paramount importance for the medical field, as it opens new opportunities for solving complex diagnostic tasks at an innovative technological level. The integration of deep learning technologies into the processes of extracting somatoscopic data not only enhances diagnostic efficiency but also creates prerequisites for the development of new decision support systems that optimize medical practice.

Р ОЛЬ ТВОРЧЕСКИХ ИНДУСТРИЙ В КРЕАТИВНОЙ ЭКОНОМИКЕ САНКТ-ПЕТЕРБУРГА В НАЧАЛЕ 2020-Х ГОДОВ

The development of the “creativity economy” of St. Petersburg in the early 2020s reflects the significant potential of the city’s creative space, which has been emerging since the 2000s in various spheres of modern culture – design and architecture, art and fashion, cinema and television, music and exhibition business, advertising and marketing, interactive media and video games – which will allow the city on the Neva in the foreseeable future to become a leader in the creative industries of Russia in order to serve as a resource influencing modernization processes, both in the economy and in culture. The legislator generates favorable opportunities for this, in particular, the Fundamentals of State Cultural Policy notes the importance of interconnected processes to “create conditions for the development of creative industries”, the production of “economic values in the process of creative activity”, which are focused on “capitalization of cultural products and their presentation on the market”. Legal deci- sions in St. Petersburg comprehensively support the spheres of creative industries, influencing their innovative soil, communication and information space, stimulate the environment, influence the market and modernize the principles of social partnership with- in the boundaries of government, business and culture in order to improve the quality of life of Russian society.

The influence of information technologies on creative and critical thinking of students / La influencia de las tecnologías de la información en el pensamiento crítico y creativo de los estudiantes

Innovative information technology is developing rapidly and is penetrating many areas of life, including education. The paper measures the impact of innovative information technology, using augmented reality (AR) as an example, on the development of creativity and critical thinking among students. The study was conducted among 180 students from Tonghua Normal University in China. The research design: a pre-test and post-test experiment with a control group. The following research findings were obtained: academic knowledge of the experimental group was higher (15.73) than that of the control group (12.13). ARLE model improved critical thinking (8.77 in AR group, 7.60 in the traditional group) and creativity (593 in AR group, 570 in the traditional group). The resulting data demonstrated the effectiveness of the proposed model of learning with the augmented reality technology. The research findings have practical implications. For example, they may be used to create new augmented reality apps for other disciplines and majors. The study presents recommendations on the development of creative and critical thinking, which teachers of various disciplines can apply in practice. The impact of other digital tools in education needs to be carefully studied to determine their effectiveness.

Technological innovations and sustainability: Shaping the future of smart cities in urban planning

Smart cities have surfaced as pioneers in new urban planning practices during this era of increased urbanization rates. These advanced technologies have been implemented to improve life and solve many problems we are facing nowadays. This study seeks to investigate smart cities that can be developed in their advantages and disadvantages, as well as opportunities and threats. The main goal is to make technology more evenly accessible and utilizable within different urban neighborhoods. Our approach to analysing smart cities is multidisciplinary, including several sectors like urban planning, green city programmes, innovative urban enterprises, and information and communication technology (ICT). The study introduces eight novel models and integrates them into a comprehensive framework to assess smart cities, offering several possible applications. Findings indicate that digital technology and the Internet of Things (IoT) can significantly transform urban dynamics, per the findings. Conversely, they emphasise significant security, privacy, and economic parity concerns. The success and widespread implementation of innovative city projects will depend on how these challenges are resolved. It is imperative to tackle these issues to ensure the ongoing feasibility of intelligent cities as a viable choice for urban development. This study emphasises the need for a well-rounded approach that maximises benefits and minimises risks to promote inclusive, safe, and equitable urban environments via smart city advancements.

Conceptual Provisions for Innovative Information Modelling in Construction

Conceptual Provisions for Innovative Information Modelling in Construction

Creation and functioning of the information-rich space of biological and ecological education of the Technopark "Quantorium" in the conditions of integration of interaction between schools and pedagogical University

The publication reflects the solution of the task of creating a Technopark space functioning on the basis of the latest information, communication and IT technologies for the implementation of modern biological and environmental education in the school-university system using the resources of the Quantorium Technopark. The authors of the study discuss the importance of integrating modern technologies and resources into the educational process in order to increase the effectiveness of learning and the practical applicability of knowledge in this field. The purpose of the article is to describe the concept of an information–rich technological space of biological and environmental education and the principles of its implementation on the basis of the Technopark “Quantorium”. The research methodology is based on the principles of developing training courses and educational and methodological support for them, involving the preparation of educational programs designed to implement innovative methods and the latest technologies in the field of biology, bioengineering, biotechnology and ecology; the use of laboratory and practical work, as well as large-scale application of biological and environmental experiments based on the use of technical resources of the Technopark. The results of the study. The paper analyzes in detail the main components of the technological information-rich space, including information systems, equipment and software used to develop training courses and laboratory work on environmental and biological topics. The role of the Technopark “Quantorium” as a center for innovation and support of educational projects, contributing to the introduction of modern educational technologies, is also considered. In their article, the researchers present the concept of an innovative information-rich space for the practical implementation of biological and environmental education. It is based on the multidisciplinary integrated application of all the resources of the Technopark “Quantorium”. The implementation of this concept will create an effective and innovative information and educational environment for school students and pedagogical university students, contributing to the development of environmental awareness and the training of qualified specialists in the field of ecology and biology.

Source identification, characteristics, and spatial distribution of airborne microplastic deposition in Lahore City, Pakistan.

A large volume of atmospheric microplastics (MPs) has been observed worldwide and is considered an emerging global environmental issue. Nevertheless, no significant assessment of the atmospheric deposition of MPs in Pakistan has been reported yet. The present study was designed to highlight the source, type, and spatial distribution of MPs in atmospheric fallout in Lahore, Pakistan. A total of 23 sites were sampled in Lahore with a heterogeneous background of human activities. All samples were collected in a box with a one-foot depth fitted with a steel tray of 0.1 m2 at the bottom. Fenton's reagent and hydrogen peroxide were used to remove organic matter, and sodium chloride for density separation, while the MPs were quantified through a stereomicroscope, and polymers were identified through ATR-FTIR spectroscopy. The highest deposition rate (particles/m2/day) was observed at Badami Bagh, i.e., 6819, followed by Mall Road 4414, and Chung 4263, while the lowest was in Sabzazaar (i.e., 524) and Township (1047) with an average deposition rate of 2340 ± 1392. Among the MPs, the major portion was fiber, i.e., 96%, while fragment was 1.9%, sheets 0.78%, foams 1.12%, beads 0.04%, and other MPs 0.06%. At all sampling sites, 20 different types of polymers were identified with different percentages, of which polyester fibers were predominant with an abundance of 96.09% associated with clothes and textiles. A high frequency of MPs was found in populated areas with dense traffic, plastic wastes, household plastic materials, and mismanagement of wastes, which accelerates the atmospheric deposition of airborne microplastics. Evaluation and characterization of MP help assess health and environmental impacts, cleanup efforts, and guiding regulations. It also provides valuable information for waste management innovation to reduce plastic pollution.

Regional Innovation Sustainability Strategy through Integrated Innovation Governance: Case Study in Sukabumi City

The sustainability of regional innovation is a problem in Sukabumi City, because the capacity and capability of human resources are still very limited and also the existing regional innovation system has not been integrated with each other. The purpose of this study is to identify the sustainability factors of regional innovation in Sukabumi City, analyze the sustainability process of regional innovation in Sukabum City. In this research on regional innovation sustainability strategies in Sukabumi City, researchers use exploration methods. Gulo (2010: 18), based on the results of the analysis, there are several factors that affect the sustainability of innovation in Sukabumi City, factors that support the sustainability of innovation in Sukabumi City, namely: resources, management systems, policies, leadership, and community participation. There is one important thing that becomes the findings of this research for the sustainability of innovation in Sukabumi City, namely Integrated Innovation Governance. Integrated Innovation Governance is an important part, because it involves easy public access to innovation. The recommendations of this study are the integration of innovation data into one innovation system (directory) through the expansion of data networks, the existence of documentation facilities and socialization of innovation results from innovation networks / stakeholders, the existence of easier facilities for the public to access innovation results, becoming an innovation information system to collect and store information on innovation results from all innovation networks, becoming a system for evaluation and selection of all innovations within the Sukabumi City Government.

China's cognitive bias premium: An exploration of innovation information

The complexity of innovation information often results in investors' cognitive bias, manifesting as an imbalance in the significance attributed to innovation quantity versus innovation quality. Based on investor cognitive bias, this paper explores the problem of innovation pricing in China's A-share market. Empirical findings indicate that cognitive bias creates a premium, primarily driven by mispricing. Moreover, we contend that mispricing originates from the innovation information environment and firms' innovation strategy. Our heterogeneity analysis indicates that the cognitive bias premium is more pronounced in high-tech industries, firms with lower market capitalization, and those facing stronger financial constraints.

Innovative Solutions for High School Inventory Management: An Information System Approach

This paper explores the development and implementation of an innovative information system designed to enhance inventory management in high schools. Traditional inventory methods, often reliant on manual tracking, are prone to errors and inefficiencies, which can hinder resource allocation and decision-making. By adopting an information system approach, schools can automate processes, improve data accuracy, and provide real-time access to inventory information. The study outlines key features such as real-time tracking, automated alerts, and role-based access controls, which are critical to the system's effectiveness. The results demonstrate significant improvements in workflow efficiency, data accuracy, and overall resource management. Despite the challenges associated with system implementation, including cost and training requirements, the benefits make this approach a compelling solution for modernizing high school inventory practices. The paper concludes with recommendations for broader adoption and further research to optimize these systems for educational settings.

Analysis of countermeasures for improving the quality of college students’ entrepreneurship by deep learning and blockchain technology

This study seeks to enhance the entrepreneurial quality of college students by introducing advanced technologies such as deep learning and blockchain. A student majoring in electronic information at a university is the research object. Based on the background of the Internet of Things and blockchain technology, the innovation and entrepreneurship information data platform for college students is constructed. The results show that the α values of students’ background, students’ professional ability, students’ practical ability, and students’ development ability are greater than 0.7. When determining the number of neurons in the hidden layer, the training error curve decreases continuously. The test error rises and then decreases when the number of neurons in the hidden layer is 10, 11, and 12. The Levenberg-Marquardt algorithm, selected as the training function, exhibits optimal performance with a training step count of 1,000 and achieves a performance score of 4.9. The actual values of the enhanced BPNN align closely with the expected values, demonstrating minimal deviation. The findings emphasize the importance for students in electronic information majors to actively engage in diverse social practices. This study serves as a valuable reference for enhancing the entrepreneurial quality of college students.

Enhancing sustainable fit between corporate social responsibility and innovation: Implications for firm performance

AbstractDespite several studies on corporate social responsibility (CSR) and innovation on firm performance, the extent to which different CSR practices interacts with distinct innovation types in enhancing firm performance remains underexplored. We draw on contingency theory to examine how internal and external CSR interacts with exploitative and explorative innovation to improve firm performance. We discuss the interaction effects using a panel dataset of 1156 publicly listed Chinese firms that disclosed CSR and innovation information from 2008 to 2019. The results indicate that firms with high‐internal CSR benefit to a greater extent from explorative innovation than from exploitative innovation as a means of enhancing performance. In contrast, firms with high‐external CSR benefit to a greater extent from exploitative innovation than from explorative innovation to improve performance. We contribute to strategy and CSR literature by revealing how firms match specific CSR practices with distinct innovation types to enhance firm performance.

An empirical study on green innovation and ESG information disclosure of listed companies in China

An empirical study on green innovation and ESG information disclosure of listed companies in China

Innovative information processes in the aviation industry

Innovative information and other numerous developments resulting from the application process of digitalization constitute a comprehensive structure that is important for any industry, and for the aviation industry in particular. This special relevance stems primarily from the defining characteristic of the aviation industry - the ability to rapidly develop, and is also supported by such important management components as the cost structure, safety and intensity of competition, which play an equally important role both for the domestic aviation industry and for global aviation giants. In the era of large-scale digitalization, the aviation IT industry is facing a number of challenges related to the combination of new distribution channels, social networks, Big data, cloud technologies, etc. One of the main challenges of the time is the need to solve the security problem when software components are distributed and operated in hybrid clouds, the providers of which may be independent from each other. The difficulty lies not only in defining and expressing the desired level of security in software, but also in how cloud services affect security assurances in the aviation industry. However, effective digitalization does not begin with the introduction of the latest technologies, but with the transformation of organizations in order to use the potential of digital solutions.

Peer Effects of Corporate Disclosures: Evidence From the Registration-Based IPO System in China

China launched the registration-based IPO system in 2019 whereby all firms listed on the newly established STAR board (“peer firms”) are required to disclose specific innovation and industry-related information in their prospectus. Using this event as a quasi-experiment, our study investigates the causal effects of peer firms’ disclosures on individual firms’ disclosure strategy. We find that the precision of individual firms’ management earnings forecast (MEF), both its form and width, significantly decreases when peer firms disclose more information during the IPO period. In cross-sectional analyses, we find this effect to be more pronounced for individual firms that are likely to experience greater competitive pressure from industry peer firms and firms with higher risks and performance uncertainty that make them more cautious to external competitive pressure. This result suggests that peer firms’ disclosures induce greater competitive pressure and uncertainty about future firm performance, triggering managers of individual firms to adopt a more cautious disclosure strategy. Overall, our study extends the literature on the peer effects in corporate disclosure decisions and documents potential unintended consequences of mandatory disclosure policies.

Artificial nociceptor based on interface engineered ferroelectric volatile memristor

Recent advancements in neuromorphic computing driven by memristors, which emulate biological synapses and neurons, have spurred the development of innovative information technologies. To extend memristor applications to artificial nervous systems, electronic receptors are crucial for converting external stimuli into signals for the internal nervous system. Key requirements for integrating neuron devices into neuromorphic computing include achieving threshold behavior, minimizing power consumption, and ensuring compatibility with complementary metal-oxide semiconductor (CMOS) technology. Hafnium-based ferroelectric memristors are known for their robust ferroelectric properties at nanoscales and compatibility with CMOS technology. However, their non-volatile resistive switching has historically limited their suitability for neuron sensory applications requiring threshold switching. This study demonstrates threshold switching behavior in a TiN/Hf0.67Zr0.33O2(HZO)/TiOx/TiN heterostructure by incorporating a nanoscale TiOx interfacial layer as an oxygen reservoir. This layer facilitates the formation of oxygen vacancies within the ferroelectric HZO layer, serving as internal charge trap sites. As a result, hafnium-based ferroelectric memristors exhibit volatile switching characteristics, enabling them to function as nociceptive devices through internal charge trapping and detrapping mechanisms. These volatile memristors are suitable for artificial nociceptor systems requiring responses such as threshold detection, relaxation, allodynia, and hyperalgesia to external stimuli. This capability opens avenues for developing advanced humanoid robots capable of rapid adaptation and response in challenging environments such as outer space or hazardous conditions, leveraging real-time sensory processing for effective operation and survival.

Analyst tracking and innovation inconsistency in companies

Disclosing corporate innovation information plays a crucial role in investors’ decision-making. It is important to regulate the consistency between a company’s words and actions to ensure that their narrative innovation disclosures accurately reflect their innovation activities. This study utilizes data from Chinese A-share listed companies from 2011 to 2022 and explores the governance role of analyst coverage on corporate innovation inconsistency from a flexible governance perspective. The research finds that analyst tracking promotes a company’s innovation inconsistency of “saying less and doing more” through the information effect and suppresses “saying more and doing less” through the monitoring effect. Further, analysts who work harder, have higher education levels, are more motivated, and demonstrate greater independence and objectivity significantly impact companies’ innovation inconsistency. This study is of great theoretical and practical significance for understanding innovation inconsistency in companies, as well as the role of analysts in the capital market.

Investigating the influence of energy dynamics on price forecasts in tropical and traditional agricultural futures markets

ABSTRACT This research aims to investigate the intricate dynamics between energy futures prices and both tropical and traditional commodities futures prices, with a particular focus on the critical role of oil futures prices in predicting the trajectory of agricultural futures prices. The study employs the Dynamic Conditional Correlation-Multivariate Generalized Autoregressive Conditional Heteroskedasticity (DCC-MGARCH) model to analyse the interplay among oil and agricultural futures price series over 2008:01–2021:06. Additionally, it incorporates the innovative Spatio-temporal Information Recombination Hypergraph Neural Network (STIR-HGNN) model to highlight the differences in how energy futures prices predict tropical and traditional agricultural futures prices. The findings reveal numerous connections between oil prices and both tropical and traditional agricultural futures prices, underscoring the significant role of oil prices in forecasting agricultural futures price movements. The empirical insights from this study provide valuable guidance for futures market participants, encouraging them to use these findings to refine and optimize their market strategies, thus enhancing their ability to navigate and capitalize on the complexities of these interconnected markets.

How efficient are Indian banks? An application of stochastic frontier analysis

Purpose This study aims to investigate the efficiency of Indian commercial banks from 2002 to 2018 using the stochastic frontier analysis. Design/methodology/approach This study uses the parametric approach of the stochastic frontier to examine the technical efficiency of banks acknowledging exogenous shocks, omitted variables and measurement errors, filling a gap in the existing financial literature. The scope of this study was constrained to 71 scheduled commercial banks to make it manageable and productive with 1,036 observations. Findings The results show that the mean technical efficiency of new private banks remained constant at 92.7% during the study period because of technology diffusion in banking systems. The technical efficiency of the nationalized, old private and foreign banks has enhanced over the period because of the efficient utilization of various innovative information technology services such as mobile banking, cheque truncation system, magnetic ink character recognition. However, the foreign banks are still laggards with a mean technical efficiency of 81.7%. The empirical findings suggest that new private sector banks depict higher efficiency than nationalized, old private and foreign banks. Research limitations/implications This study’s sample represents all categories of banks (public, private and foreign) including the banks that merged or consolidated during the period of study. To achieve the desired results, the authors incorporate the consolidated and merged banks in their data set. Further, the authors excluded all scheduled small finance banks and scheduled payment banks from their analysis, as these entities commenced operations post-2015. Additionally, the authors also excluded regional rural banks because of their distinct mandate aimed at servicing the rural populace and agricultural sector. Originality/value This study contributes to the literature on the performance of conventional banks in general and emerging markets, in particular, using the most recent data and covering a relatively long period using the stochastic frontier approach.