Advent Research Articles

Pengaruh Struktur Kepemilikan, Penerapan Digital Banking, dan Investasi Teknologi Informasi terhadap Kinerja Intellectual Capital: Studi Empiris pada Perusahaan Perbankan yang Terdaftar di BEI Tahun 2017-2021

The study aims to prove the effect of the implementation of digital banking, investment in information technology, and ownership structure such as institutional ownership and foreign ownership on intellectual capital performance. The population in this study was banking sector company in Indonesia Stock Exchange in 2017- 2021. Sample was determined using the purposive sampling method. Data analysis technique for hypothesis testing using multiple regression analysis. The of statistical analysis show that foreign ownership has no significant effect while institutional ownership, the implementation of digital banking, and investment in information technology have positive and significant effect to intellectual capital performance.

No evidence for a privileged role of global ensemble statistics in rapid scene perception: A registered replication attempt.

The nature of visual processes underlying scene perception remains a hotly debated topic. According to one view, scene and object perception rely on similar neural mechanisms, and their processing pathways are tightly interlinked. According to another, scene gist might follow a separate pathway, relying primarily on global image properties. Recently, this latter idea has been supported with a set of experiments using content priming as a probe into scene and object perception (Brady et al. Journal of Experimental Psychology: Human Perception and Performance, 43, 1160-1176, 2017). The experiments have shown that preserving only structureless global ensemble texture information in the images of scenes could support rapid scene perception; however, preserving the same information in the images of objects failed to support object perception. We were intrigued by these results, since they are at odds with findings showing that scene content is primarily carried by the explicit encoding of scene structure as represented, for instance, by contours and their properties. In an attempt to reconcile these results, we attempted to replicate the experiments. In our replication experiment, we failed to find any evidence for a privileged use of texture information for scene as opposed to object primes. We conclude that there is no sufficient evidence for any fundamental differences in the processing pathways for object and scene perception: both rely on structural features that describe spatial relationships between constituent parts as well as texture information. To address this issue in the most rigorous manner possible, we here present the results of both a pilot experiment and a pre-registered replication attempt.

Disaggregated effects of artificial intelligence, online and mobile banking on customer satisfaction in banks: An analysis using structural equation modelling

In the Fourth Industrial Revolution (4IR) era, the rapid digitalisation of services poses both opportunities and challenges for the banking sector. This study addresses how adopting artificial intelligence (AI) and online and mobile banking advancements can influence customer satisfaction, particularly in Kaduna State, Nigeria. Despite significant investments in AI and digital banking technologies, banks often struggle to align these innovations with customer expectations and satisfaction. Using Structural Equation Modeling (SEM), this research investigates the impact of customer satisfaction with online banking (C_O) on AI integration (I_A) and mobile banking convenience (C_M). The SEM model reveals that customer satisfaction with online banking significantly influences AI integration (path coefficient of 0.40) and mobile banking convenience (path coefficient of 0.68). These results highlight a crucial problem: while technological advancements in banking are growing, their effectiveness is highly dependent on customer satisfaction with existing digital services. The study underscores the need for banks to prioritise enhancing online banking experiences as a strategic lever to improve AI integration and mobile banking convenience. Consequently, the research recommends that Nigerian banks develop comprehensive frameworks to evaluate and optimise their technology integration strategies, ensuring that technological innovations align with customer needs and expectations in the rapidly evolving digital landscape.

The Past, Present, and Future of Clickers: A Review

Classroom response technologies commonly called “clickers” have been a popular tool for teaching in many disciplines, even required by some courses. Despite this excitement and corresponding investment in clicker technology, scholars disagree on the value of clickers. To help support teachers who utilize or are interested in using clickers, we explore the past, present, and future of clickers in education. This manuscript provides a literature review of how clickers are used, the benefits and challenges, and suggestions on the implementation of clicker technologies. Utilizing five research databases and a wide range of search terms, two general trends for clicker use became apparent: traditional classrooms that use clickers to enhance them and classrooms integrating clickers with more novel pedagogical approaches. After separating the papers into groups based on the trend they follow, the benefits and challenges were identified and recorded. In turn, we summarize what research has to say regarding both teachers and students for each of these primary outcomes. Building off clicker research both past and present, this review then looks toward the future by providing suggestions for overcoming the challenges faced by students and teachers when using clickers. Furthermore, we recommend important directions to consider for future research on clickers, including the need for more empirical studies of how different uses of clickers can benefit different learners in increasingly equitable ways.

Sustainable inventory model with controlled temperature for deteriorating products under preservation technology

The disaster or epidemic has created a terrible situation in front of the whole world. This study saves the Corona vaccine's quality and keeps its demand in mind. This study develops an inventory model for deteriorating products with preservation technology investment under ramp-type demand. Reducing the deterioration rate of items reduces the number of waste items, which is beneficial for the environment. The demand increases at the ramp-type demand rate at the start, and then the market tends to a constant rate until the end of the inventory cycle. Retailers are attempting to reduce emissions, which impacts inventory levels. As a result, the impact of carbon emissions from holding and deterioration costs has been investigated in this study. This study allows for partially backlogging and shortages. The numerical part shows the minimized total cost of this study. The numerical findings indicate that the value of total cost increases due to carbon emissions. The study is analyzed for two cases: Case I shows a difference of 0.45% in total cost due to carbon emission, while Case II shows a difference of 0.20% in total cost due to carbon emission. Carbon emissions and preservation technology have a significant impact on environmental preservation. Finally, numerical examples and graph representation for convexity of total cost and sensitivity analysis are provided to illustrate.

Leveraging Genomic Data for Infectious Disease Surveillance and Personalized Medicine: Advances in Public Health Genomics and COVID-19 Pathway Analysis

In public health, the arrival of genomic data greatly enhanced infectious disease surveillance, personalised medicine and the global response to pandemics. This Review examines how genomic sequencing became a vital tool for identifying pathogens, tracking virus evolution, and tracing transmission chains, with case studies on COVID-19 variants such as Delta and Omicron. Genomic sequencing has also led to breakthroughs in personalised medicine and pharmacogenomics, whereby drug efficacy and adverse reactions are optimised for individual patients. Genomic surveillance is now a critical tool for detecting emergent threats, monitoring disease spread, and evaluating the efficacy of public health interventions, from contact tracing to vaccines. These genomic approaches have saved thousands of lives during the global COVID-19 pandemic. The paper ends on a positive note about the advances in public health genomics and underscores the value of continuing investment in genomic technologies to safeguard global health security.

Rouvière's Sulcus as a Landmark for a Safe Laparoscopic Cholecystectomy: An Interim Analysis of a Multicenter Cross-sectional Study on the Prevalence and Morphologic Type of Rouvière's Sulcus in the Italian Population.

Laparoscopic cholecystectomy is the gold standard in the treatment of symptomatic gallstones. The large number of gallbladders removed every year is not fully consistent with the excessively high incidence of iatrogenic bile duct injury (IBDI). Several strategies have been suggested to reduce this risk. Among them, the use of extra biliary anatomic structures, such as the Rouvière's sulcus, as a landmark to guide the surgeon during dissection has been proposed as a means to prevent IBDI. The main aim of the present paper is the evaluation of the prevalence of Rouvière's sulcus (RS) and its anatomic variants in a given population. This observational, cross-sectional, and multicenter study has been conducted at the Department of Digestive and Emergency Surgery of the "Azienda Ospedaliera Santa Maria," Terni (Italy), at the Department of Surgical Sciences of the "Azienda Ospedaliera Perugia," Perugia (Italy) and at the Department of Emergency and Trauma Surgery of the "Policlinico Umberto I," Rome (Italy). Intraoperative images of 111 patients undergoing laparoscopic cholecystectomy were analyzed to identify the presence and type of RS, according to the Singh-Prasad classification and the Dahmane classification. RS was present in 93 (83.8%) patients. Singh-Prasad type 1A is present in 48.4% of patients, type 1B in 25.8%, type 2 in 12.9% and type 3 in 12.9%. Dahmane's open type is present in 48.4% of patients and fused type in 51.6%. Due to its high prevalence, RS can be used as an anatomic landmark and probably reduces the incidence of IBDI during laparoscopic cholecystectomy.

Research on Government Dynamic Strategies for Mining Technology Investment of Mineral Resource Enterprises

As a large mineral resource consuming country, it is of great strategic significance to effectively improve the efficiency of China’s mineral resource exploitation and reduce the waste of exploitation to achieve sustainable development. The purpose of this paper is to examine how governments can incentivize enterprises to invest in mining technology to improve mineral resource recovery rates under both process subsidy policy and outcome incentive policy, and to comparatively analyze which policy is more effective in increasing mineral resource enterprises’ investment in mining technology. We construct a differential game model of the government’s incentive policy for mining technology investment in mineral resource enterprise. The results show the following. (1) For mineral resources with low marginal returns, both process subsidy and outcome incentive policies can encourage the enterprise to increase investment in mining technology. (2) For scarce strategic resources, the process subsidy policy has a better incentive effect when the marginal returns of mineral resources are high, and the outcome incentive policy has a better incentive effect when the marginal returns are low. (3) Mineral resource enterprise has higher recovery rates under the process subsidy policy.

Assessing the Impact of Digital Transformation on Access, User Experience, and Knowledge Management in Academic Libraries

This study investigates the impact of digital transformation on access, user experience, and knowledge management in academic libraries. Findings indicate significant improvements in resource accessibility and user satisfaction with digital tools, although challenges remain in interface design and digital literacy. The introduction of AI-driven knowledge management systems has enhanced the accuracy and efficiency of information retrieval. Despite progress, issues such as budget constraints and the need for inclusivity in digital tools highlight areas for continued development. This research emphasizes the need for further investments in technology, staff training, and inclusive practices. .

The Low Level of Digital Literacy in Indonesia: An Analysis of Online Media Content

Background of the study: The low level of digital literacy among Indonesians poses a significant challenge in the era of global digitization, particularly due to the lack of access to and understanding of information technology required to make effective use of digital libraries. Purpose: Identify factors causing low digital literacy, evaluate policies that have been implemented, and formulate effective strategies to increase digital library utilization in Indonesia. Method: This study uses a qualitative approach by analyzing online news using the keyword ‘digital literacy’, to explore the factors that lead to low digital literacy in Indonesia. Data analysis methods included coding, theme building, data reduction, and data display to identify patterns and reasons behind this phenomenon. Findings: This research reveals that Indonesia's low digital literacy is caused by a lack of infrastructure, a lack of educational focus, and low awareness of social media ethics. Collaboration between the government, academic institutions, and society is needed through technology investment, education reform, and awareness campaigns. Conclusion: Recommended follow-up includes training, digital infrastructure development, and effective awareness campaigns to improve digital literacy in Indonesia.

Algorithmic futuring: predictive infrastructures of valuation and investment in the assetization of edtech

ABSTRACT Futures of education are increasingly defined through predictive technologies and methods. We conceptualize ‘algorithmic futuring’ as the use of data-driven digital methods and predictive infrastructures to anticipate educational futures and animate actions in the present towards their materialization. Specifically, we focus on algorithmic futuring in the education technology investment industry, and the role of predictive infrastructures of valuation and investment in the assetization of edtech. Edtech investment actors make predictions based on the calculated future asset value of digital technologies. Methods and narratives of algorithmic futuring produced through predictive infrastructures are intended to render an assetized future of education seemingly attractive, attainable, and actionable. Our analysis foregrounds three forms of algorithmic futuring practised by an edtech investment organization: forecasting targets; managing uncertainty; and provoking assetization. Each has significant impacts on what futures are put into motion in the present, and exploit a gap in public investment in edtech futures.

Green Technology Investment and Production Decisions Considering Stochastic Demand and Firms' Decision Preferences Under Cap‐and‐Trade Regulation

ABSTRACTThis paper investigates how finite rational firms optimally respond to market potential under cap‐and‐trade regulation, considering stochastic demand. Using the mean–variance model framework, we develop an optimization model for green technology investment and production by finite rational firms with different decision‐making preferences. The main results indicate: (1) Under stable demand, firms investing in green technology gain more profits and consumer surplus, however, the effectiveness of carbon emission reduction depends on the market potential size. (2) Under stochastic demand, optimal decisions resulting from firms' varying decision preferences systematically deviate from those of risk‐neutral firms and often demonstrate firms' risk‐averse tendencies that lean towards conservatism. As external factors change, there can even be a reversal in technology investment with an increase in demand uncertainty that amplifies this systematic deviation. (3) Taking firms with different decision‐making preferences as the starting point, this study further analyses the distortion effect of the firm's risk attitude on the optimal technology investment and production decisions, enriching the related research on the joint decision‐making risk model of clean production. And it is more pertinent to the complex situation firms face in the real situation with decision‐making. (4) This study provides a theoretical basis and practical reference for the finite rational firms facing green technology investment choices. Considering the risk‐averse characteristics of firms, this study suggests that the government should establish a risk‐sharing mechanism to weaken the deviation of stochastic demand from the optimal decision‐making of firms or implement certain subsidy policies to protect the profit level of firms.

Don’t overdo it with blockchain – understanding the impact of blockchain on users’ security perception

PurposeBlockchain technology has been labeled as the most disruptive technological innovation of the current decade due to its impact on almost every major industry. Based on privacy calculus theory and prior adoption literature on emerging technologies, this research investigates the impact of blockchain technology in the consumer technology segment. It elaborated on the mechanism through which blockchain technology influences users’ willingness to share information with technology products enabled by blockchain.Design/methodology/approachTaking a heterogeneous pool of users, this study conducted multiple experiments with the application of blockchain (vs. regular database) technology to high (vs. low) sensitive data to study the impact of blockchain perception on users’ information-sharing tendencies.FindingsThrough a mediated moderation analysis, the result shows that the use of blockchain technology enhances the sense of security among users. However, the impact of this heightened sense of security only develops a higher willingness to share information when the data is highly sensitive.Practical implicationsThe research reflects on the perception of blockchain technology and the leading impact on willingness to share information with firms. This could be a critical criterion for determining investment in blockchain technologies for consumer products, particularly based on the sensitivity of the data the consumer is sharing.Originality/valueThis research focuses on the perception of blockchain technology among consumers and its impact on consumers’ decision-making related to their data sharing. People have a higher sense of safety when it comes to blockchain-enabled products. However, we find that it would not be the same for all contexts, and the sensitivity of the data collected would have an impact on this relationship and consumers’ data-sharing decisions.

Modern Challenges and Prospects for information and communication technologies development in Russia

This study analyzes the volume of data transmitted through fixed and mobile networks between 2011 and 2022. It was found that during this period, the volume of data transmitted via fixed networks increased by 10.5 times, while data through mobile networks grew by 152 times. The most significant growth was observed in the mobile network segment, driven by technological advancements and the increasing number of mobile internet users. The study highlights that the growth in data volumes creates opportunities for telecom operators and digital solution developers, including infrastructure development and new digital services. However, this growth also poses challenges such as network strain, the need for investment in new technologies, and heightened risks related to data security and digital inequality. The findings are important for assessing current trends in telecommunications and planning future infrastructure development.

Artificial Intelligence (AI) and Health Communication Policy in Nigeria: Challenges and Prospects

Advances in Artificial Intelligence (AI) are reshaping health communication worldwide, a key aspect of enhancing public health. This study analyzed current health communication policies to pinpoint areas where AI-driven approaches are yet to be addressed. In Nigeria, integrating AI into health communication policies presents both opportunities and hurdles. The study examined how AI can boost health communication initiatives in Nigeria, particularly through AI-powered tools that enhance the spread of health messages, patient education, and public awareness campaigns. Additionally, the study highlighted challenges in implementing AI technologies, including limited infrastructure, inadequate data management, and a shortage of skilled professionals. The paper also presented the potential of Artificial Intelligence (AI) to transform health communication. It suggested policy guidelines to support its integration while reducing risks. Additionally, it recommended policy changes, training, and cooperation among stakeholders to leverage AI's power in health communication. In Nigeria, the outlook for AI in health communication is optimistic, assuming focused investments in technology, training, and regulatory reforms.

Digital Information Ecosystems in Modern Care Coordination and Patient Care Pathways and the Challenges and Opportunities for AI Solutions

The integration of digital technologies into health care has significantly enhanced the efficiency and effectiveness of care coordination. Our perspective paper explores the digital information ecosystems in modern care coordination, focusing on the processes of information generation, updating, transmission, and exchange along a patient’s care pathway. We identify several challenges within this ecosystem, including interoperability issues, information silos, hard-to-map patient care journeys, increased workload on health care professionals, coordination and communication gaps, and compliance with privacy regulations. These challenges are often associated with inefficiencies and diminished care quality. We also examine how emerging artificial intelligence (AI) tools have the potential to enhance the management of patient information flow. Specifically, AI can boost interoperability across diverse health systems; optimize and monitor patient care pathways; improve information retrieval and care transitions; humanize health care by integrating patients’ desired outcomes and patient-reported outcome measures; and optimize clinical workflows, resource allocation, and digital tool usability and user experiences. By strategically leveraging AI, health care systems can establish a more robust and responsive digital information ecosystem, improving care coordination and patient outcomes. This perspective underscores the importance of continued research and investment in AI technologies in patient care pathways. We advocate for a thoughtful integration of AI into health care practices to fully realize its potential in revolutionizing care coordination.

Encouraging registered reports at the Canadian Journal of Experimental Psychology (CJEP): An invited tutorial by Oshiro et al. (2024).

Continuing Canadian Journal of Experimental Psychology's ongoing commitment to Open Science, we invited Oshiro et al. (2024) to submit a peer-reviewed tutorial of the typical format and to offer key pieces of advice when preparing Registered Reports. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Small And Medium Size Enterprises (Smes), Made In Cameroon, Import-Substitution: Possible Or Mirage?

The objective of this research was to apply scientific methodology to assess the capacity in term of Technical, Innovation, and Financial of Small and Medium Sizes Enterprises (SMEs) in Cameroon to face the challenge of Import Substitution with “Made in Cameroon” products and services. This was done through analyzing data on a sample which was randomly selected from SMES operating in different sectors in Cameroon. A structured survey questionnaire was used to collect quantitative data on SME efforts on key variables such as SME size, years in operation, investment in technology, R&D expenditure, access to finance, and perceptions of government support. The Mean Computation analyses allow us to compare two or more important variables to achieve the main objective, while the Correlation Analyses bring us to analyses the relationships or the interdependencies that exist between a given set of variables. The study concludes that the main findings are in line with our hypotheses and show that using strategies to replace imports can help increase local production, particularly in manufacturing sector. To support SMEs a pack of recommendations was proposed to enhance government support toward SMEs

Unveiling the Green Truth: How Transparent Are Malaysian Manufacturing Companies About Their Carbon Footprint

Environmental sustainability has become a key concern for businesses worldwide, with expectations that they take responsibility for their carbon emissions and environmental effects. Reducing carbon emissions is critical for businesses due to companies' regulatory pressures and market expectations. Malaysia increased its mitigation ambition with an unconditional target to cut carbon intensity against GDP by 45% by 2030 compared to 2005 levels. This study aims to evaluate the extent of carbon footprint disclosure among manufacturing companies in Malaysia. Companies listed in Bursa Malaysia were chosen as the sample data in this study. The result of content analysis, approximately 18.97%, 269 of respondents are willing to disclose their carbon footprint information, suggesting a relatively low level of carbon footprint reporting. The policymakers should provide incentives for investment in green technology and enact strict regulations to encourage more companies to engage in carbon reporting.

From Policy to Practice: Evaluating the Role of Private-Sector Champions Like Elon Musk in Shaping Trump's 2.0 Climate Agenda

This paper explores the prospective influence of private-sector leaders, particularly Elon Musk, on the formulation of climate and energy policy in a possible second term of President Donald Trump. Historically, the goals of the Trump administration have been viewed as opposed to environmental advocacy; yet, this analysis explores the potential for public-private partnerships that reconcile economic objectives with climate-positive results. Musk's enterprises—Tesla, SpaceX, and SolarCity—are transforming clean energy, and his impact on federal climate policies may initiate a new phase of environmentally sustainable economic development within conservative administration. This study analyzes case studies where Musk has collaborated with public authorities to tackle environmental and energy issues, highlighting practical strategies for partnership. Potential synergies are seen in sectors including renewable energy, electric vehicle infrastructure, and sustainability-oriented manufacturing, underscoring their alignment with Trump's economic plan. Additionally, the article examines the policy mechanisms—tax incentives, regulatory reforms, and investments in clean technology—that may encourage private sector participation in a nationally endorsed climate agenda. This article advocates for a worldview in which leaders like Musk advance environmental progress by harmonizing innovation with conservative regulatory frameworks while preserving traditional economic objectives. Ultimately, it advocates for a revolutionary public-private partnership paradigm that utilizes private sector expertise to tackle climate challenges. This viewpoint enhances the current dialogue on sustainable development and the changing function of private enterprises in public policy, proposing a future where economic growth and environmental stewardship coexist within U.S. federal climate policy.