Research Opportunities Research Articles

Social media and political contention - challenges and opportunities for comparative research

ABSTRACT In this special issue, the authors theoretically, methodologically, and empirically address challenges and opportunities associated with comparative social media analysis in political contention. Actors from civil society, media, and institutional politics use social media to coordinate, mobilise, and communicate, turning public online communication into an arena of conflict that offers researchers valuable windows of observation. In this introduction to the special issue, we systematise comparative perspectives on social media and political contention. We outline the traditional comparative dimensions of space, time, platform, and case; and suggest an approach for comparison within dimensions that are less dependent on the rapidly changing social media environment and more attuned to the interconnection between social media and political contention.

Fake News Detection Datasets: A Review and Research Opportunities

Fake News Detection Datasets: A Review and Research Opportunities

QUANTUM COMPUTING FOR MARKET RESEARCH

QUANTUM COMPUTING FOR MARKET RESEARCH

Revisiting Recent Tissue Engineering Technologies in Alveolar Cleft Reconstruction.

Tissue engineering and regenerative medicine have received significant attention in treating degenerative disorders and presented unique opportunities for researchers. The latest research on tissue engineering and regenerative medicine to reconstruct the alveolar cleft has been reviewed in this study. Three approaches have been used to reconstruct alveolar cleft: Studies that used only stem cells or biomaterials and studies that reconstructed alveolar defects by tissue engineering using a combination of stem cells and biomaterials. Stem cells, biomaterials, and tissue-engineered constructs have shown promising results in the reconstruction of alveolar defects. However, some contrary issues, including stem cell durability and scaffold stability, were also observed. It seems that more prospective and comprehensive studies should be conducted to fully clarify the exact dimensions of the stem cells and tissue engineering reconstruction method in the therapy of alveolar cleft.

Navigating the path to sustainable energy transition in Oman: a systematic literature review and future research opportunities

Navigating the path to sustainable energy transition in Oman: a systematic literature review and future research opportunities

Active Learning for Data Quality Control: A Survey

Data quality plays a vital role in scientific research and decision-making across industries. Thus, it is crucial to incorporate the data quality control (DQC) process, which comprises various actions and operations to detect and correct data errors. The increasing adoption of machine learning (ML) techniques in different domains has raised concerns about data quality in the ML field. Conversely, ML’s capability to uncover complex patterns makes it suitable for addressing challenges involved in the DQC process. However, supervised learning methods demand abundant labeled data, while unsupervised learning methods heavily rely on the underlying distribution of the data. Active learning (AL) provides a promising solution by proactively selecting data points for inspection, thus reducing the burden of data labeling for domain experts. Therefore, this survey focuses on applying AL to DQC. Starting with a review of common data quality issues and solutions in the ML field, we aim to enhance the understanding of current quality assessment methods. We then present two scenarios to illustrate the adoption of AL into the DQC systems on the anomaly detection task, including pool-based and stream-based approaches. Finally, we provide the remaining challenges and research opportunities in this field.

Systems Interoperability Types: A Tertiary Study

Interoperability has been a focus of attention over at least four decades, with the emergence of several interoperability types (or levels), diverse models, frameworks, and solutions, also as a result of a continuous effort from different domains. The current heterogeneity in technologies such as blockchain, IoT and new application domains such as Industry 4.0 brings not only new interaction possibilities but also challenges for interoperability. Moreover, confusion and ambiguity in the current understanding of interoperability types exist, hampering stakeholders’ communication and decision-making. This work presents an updated panorama of software-intensive systems interoperability with particular attention to its types. For this, we conducted a tertiary study that scrutinized 37 secondary studies published from 2012 to 2023, from which we found 36 interoperability types associated with 117 different definitions, besides 13 interoperability models and six frameworks in various domains. This panorama reveals that the concern with interoperability has migrated from technical to social-technical issues going beyond the software systems’ boundary and still requiring solving many open issues. We also address the urgent actions and also potential research opportunities to leverage interoperability as a multidisciplinary research field to achieve low-coupled, cost-effective, and interoperable systems.

Understanding urban perception with visual data: A systematic review

Visual characteristics of the built environment affect how people perceive and experience cities. For a long time, many studies have examined visual perception in cities. Such efforts have accelerated in recent years due to advancements in technologies and the proliferation of relevant data (e.g., street view imagery, geo-tagged photos, videos, virtual reality, and aerial imagery). There has not been a comprehensive systematic review paper on this topic to reveal an overarching set of research trends, limitations, and future research opportunities. Such omission is plausibly due to the difficulty in reviewing a large number of relevant papers on this popular topic. In this study, we utilized machine learning techniques (i.e., natural language processing and large language models) to semi-automate the review process and reviewed 393 relevant papers. Through the review, we found that these papers can be categorized into the physical aspects of cities: greenery and water, street design, building design, landscape, public space, and the city as a whole. We also revealed that many studies conducted quantitative analyses with a recent trend of increasingly utilizing big data and advanced technologies, such as combinations of street view imagery and deep learning models. Limitations and research gaps were also identified as follows: (1) a limited scope in terms of study areas, sample size, and attributes; (2) low quality of subjective and visual data; and (3) the need for more controlled and sophisticated methods to infer more closely examined impacts of visual features on human perceptions. We suggest that future studies utilize and contribute to open data and take advantage of existing data and technologies to examine the causality of visual features on human perception. The approach developed to accelerate this review proved to be accurate, efficient, and insightful. Considering its novelty, we also describe it to enable replications in the future.

Exploring the Landscape of e-Government Maturity Models: Insights from Systematic Mapping Study and Comparative Analysis

e-Government Maturity Models are essential tools for governments to assess and improve their e-government capabilities, performance, and impact. This article offers a pioneering systematic mapping study and comparative analysis of e-Government Maturity Models proposed between 2010 and 2022, marking a significant stride in the realm of e-government research. The review focuses on these recent models and compares their approaches, frameworks, and dimensions. Previous comparison research studies conducted before 2010 are also reviewed to provide an inclusive context for understanding the evolution and advancement of e-government maturity models. The study is the first to systematically map and compare e-Government Maturity Models proposed in recent years, also comparing with the previous decade. Employing a mixed-methods approach, this article meticulously dissects and contrasts various models, shedding light on the evolution, strengths, and weaknesses of e-government maturity frameworks over more than a decade. The research contributes to the literature by revealing underlying discrepancies in current models and proposing a synthesized perspective that integrates technological advancements and administrative strategies, providing insights into opportunities for future research and practice. The findings of the study can be used to develop a new generation of e-government maturity models that are more comprehensive and relevant to the current needs of governments.

Literature Review of Digital Recruitment: How Effective is Artificial Intelligence in Selecting People?

The use of artificial intelligence in recruitment can help select candidates according to company standards through a simple, effective, and efficient process. This paper investigates how the AI implementation in the traditional recruitment process transform into the AI-based recruitment and its impact on recruitment processes. We use systematic literature review and content analysis to obtain information regarding research gaps, research limitations, and future research opportunities. We analyze 35 articles collected between 2008 and 2022 showing that AI has several benefits, including increasing the interest of candidates to apply for jobs, increasing efficiency and timeliness, reducing recruitment costs, obtaining the best candidates, and reducing bias in the recruitment process

Water Accounting

The urgent solutions required to avoid the increasingly frequent floods and droughts and many other issues regarding water access and management made water a subject that has attracted the attention of many – as they did with accounting professionals. Since businesses are among the largest consumers of freshwater worldwide, corporate engagement with water issues is required to safeguard the organization’s license to operate. Corporate Water Accounting then allows companies to determine the impacts of their water use and discharges on communities and ecosystems, evaluate their water-related material risks, track the effects of changes in their water management practices, and credibly report them to their stakeholders. Therefore, this theoretical essay addresses water issues within the accounting field by recognizing three interrelated approaches that drive corporate water accounting implementation - Water Risk, Water Resources Management, and Water Reporting. We acknowledge its concepts, some useful tools, and its most concerning challenges while tracing its current state, especially in Brazil, and our future expectations for water accounting development. Furthermore, based on the theoretical contributions discussed, we point out some challenges managers face and future research opportunities. We expect more accounting professionals and researchers to engage with corporate water accounting to overcome the gaps that challenge the field's development.

Validating the Delone and Mclean’s model in a developing country’s infectious disease pandemic context.

BackgroundThis study aimed at validating the updated DeLone and McLean’s information systems success model (D&MISS) in a developing country’s infectious disease pandemic preparedness and response context. The findings from this study are relevant to inform policies and actions for enhancing developing countries’ the Health Information System’s (HIS) performance, and specifically to improve their future pandemic readiness and response. The study sought to respond to a key research question: to what extent can the D&MISS model provide evidence to enhance the HIS’s infectious disease pandemic readiness and response in developing countries?MethodA cross-sectional study design that involved a multi-stage probability sampling approach to select eligible healthcare workers was applied. Conducted in Nigeria and Liberia, 576 primary healthcare workers, out of the proposed 600, participated, representing a response rate of 96%. The D&MISS model served as the theoretical underpinning for this study, and nine hypothesized relationships were stated before the study based on the interconnectedness of the model’s six dimensions. Structural Equation Modelling (SEM) data analysis using the Partial Least Square approach was used to determine if hypothesized relationships were supported.Results70% of the observed variance in the Net Benefit construct was explained by the predictive influence of the Use and User Satisfaction constructs. The Use construct had a slightly more substantial predictive influence than the User Satisfaction construct. Eight of the nine hypothesized relationships were supported, except for the relationship between Information Quality and Use. The relationships between System Quality and Use and User Satisfaction and Net Benefit had the highest beta coefficient, statistically significant at p < 0.05.Conclusion and relevanceThe D&MISS model demonstrated its relevance in providing evidence on the gaps of the HISs regarding future pandemic preparedness and response. However, from a future research opportunity, its enhancement and modifications with context-specific dimensions peculiar to developing countries will improve its ability to provide more context-specific evidence to improve pandemic preparedness and response for developing countries.

Development and validation of the positive evaluation core beliefs scale for social anxiety

Fear of positive evaluation (FPE) is becoming recognised as an important component of social anxiety that is distinct from fear of negative evaluation (FNE). While core belief scales exist for fear of negative evaluation (FNE), none has been developed for FPE. Therefore, this paper describes the development and validation of a measure of core beliefs that is specific to FPE. An exploratory factor analysis was performed on 60 initial items with an Australian undergraduate sample, in which a confirmatory factor analysis was performed with an independent Australian general population sample. A series of further analyses were performed to test convergent and divergent validity. The Positive Evaluation Core Beliefs Scale (PECS) emerged as a 17-item two-factor psychometrically valid measure that correlates more strongly with measurement of FPE than FNE. The PECS measure offers a new opportunity for researchers and clinicians to better explore cognitions associated with social anxiety.

“News Desertification” in Europe: Highlighting Correlations for Future Research

The Local Media for Democracy (LM4D) project is the first project that explores news deserts in Europe comprehensively. Its final report highlighted challenges and opportunities for local and community media and identified the level of risk of news deserts in the 27 European Union (EU) Member States. As a pilot project, however, its results are still preliminary and open to evaluation, and, thus, they require further discussion and corroboration. Drawing from these results, and applying a multidisciplinary approach, we extrapolated research directions for the study of news deserts in the EU. By cross-analyzing data from the LM4D dataset with other datasets, we provide a preliminary analysis of three promising lines of research: (1) the relationship between public service media quality and news deserts, (2) news deserts and the spread of disinformation, and (3) social media usage and news desertification. We conclude by pointing out the limitations of this preliminary analysis and opportunities for further research on news deserts in the EU.

Application of artificial intelligence in retail

In the context of the contemporary Industry 4.0 concept, artificial intelligence (AI) has become an integral component of human lifeʼs success, the impact of which is increa­singly difficult to overestimate today. With the advent of AI, the everyday life of individuals has noticeably transformed. Neural networks are capable of working in an algorithmic way, adapt, learn, and even generate new inven­tions within a short span of time. Since the concept of AI appeared, fervent debates have revolved around its advantages and opportu­nities for modern society, ethical frameworks of application, risks, and the negative impact of AI on various professional spheres. However, the revolutionary changes brought about by AI, enabling individuals to delegate routine tasks and freeing up time for creative endeavors, remain indisputable. Despite the high significance of previously conducted research, the state and potential opportunities of industrial application of AI remain insufficiently explored. The purpose of the study is to determine the current trends in the development of artificial intelligence, to assess the actual state of use and to justify recommendations for the future use of AI systems in the retail sector. It has been deter­mined that the introduction of AI technologies is a modern global trend and one of Ukraineʼs priorities. It has been proven that the complex realities of domestic retail development unveil opportunities for digital transformation and the intensification of AI implementation. The current state of AI development has been examined: the leading countries in artificial intelligence implementation have been identified, and the retail sector has been ranked fourth among industries with high potential for the application of advanced technologies. To gain an understanding of AI development in retail, a survey was conducted, the results of which delineated business processes where AI techno­logies are actually applied and specified the goals of their application. The priority opera­tional processes of retail enterprises for the implementation of advanced technologies have been identified and ranked by the significance of AI systems, which are most relevant to modern retail. A list of AI systems has been sorted according to their purpose and functional capa­bilities in retail.

Cash waqf innovation in Islamic financial institutions and its governance issues, case studies: Indonesia, Malaysia, Türkiye

Purpose This study aims to examine the potential for waqf innovation to be developed as products and services by Islamic financial institutions, identify the barriers and facilitators to the implementation of cash waqf governance in Indonesia, Türkiye and Malaysia, and to explore how pandemics have influenced the role of cash waqf practices in the three countries. Design/methodology/approach This study adopts a qualitative approach with an interpretative perspective, drawing on ecology theory and Ibn Khaldun’s thought. The research method includes conducting literature reviews and interviews to explore the concept and significance of cash waqf, the offerings of Islamic financial institutions and the mechanisms for good governance of cash waqf to bolster the proposed model. Findings The finding shows that a model of cash waqf governance that outlines the relationships and interactions with the goal of advancing cash waqf. The use of technology, specifically computer technology, further strengthens these interactions. Research limitations/implications This study suffers from several limitations, such as the number of countries in the sampling. Thus, future research opportunities include exploring similar initiatives in other countries and examining the connections between different sub-fields within the global cash waqf practice. Originality/value The contribution of this study serves as a guide for cash waqf organizations to promote professional, responsible and accountable management practices; reduce the risks faced by waqf managers and support them in making improvements to enhance the role of waqf in Indonesia and elsewhere; as well as provide a reference for the government and waqf agencies in promoting the importance of cash waqf governance in the country.

The evolutional aspect of change in the training conditions of neurosurgical residents

Background: The Korean Neurosurgical Society’s 60th anniversary in 2022 compelled us to reflect on the changes within the education programs of neurosurgery residents. Traditional apprenticeship has witnessed a structural shift to manual-based education, and content has transitioned from time-based to competency-based education, driven further by the implementation of the 80-hour work-per-week regulation.Current Concepts: Despite reduced training hours, neurosurgery residents strive to gain more surgical participation and research opportunities while working 80 hours per week. To address this conflicting scenario, the Korean Neurosurgical Society implemented proactive measures to enhance resident education. This included the development of a competency-based training curriculum and guidelines for supervising physicians to prepare residents with the essential skills for independence. Additionally, evaluation guidelines and feedback mechanisms were established to provide objective assessments and facilitate self-improvement. Establishing operational guidelines and developing an e-portfolio would help minimize variations in educational effects among residents.Discussion and Conclusion: Failure to adapt to the changing environment, including the 80-hour work week, by maintaining outdated training methods would result in stagnation or a decline in the efficiency of resident education. Therefore, providing a unified educational curriculum and ensuring sustainable, high-quality training according to the evaluation systems of the Korean Neurosurgical Society is essential. This curriculum must be reviewed on an ongoing basis to recognize the society’s expertise and develop educational policies based on scientific evidence and the opinions of society members.

Virtual reality tools for training in gastrointestinal endoscopy: A systematic review

BACKGROUND Virtual reality (VR) has emerged as an innovative technology in endoscopy training, providing a simulated environment that closely resembles real-life scenarios and offering trainees a valuable platform to acquire and enhance their endoscopic skills. This systematic review will critically evaluate the effectiveness and feasibility of VR-based training compared to traditional methods. AIM To evaluate the effectiveness and feasibility of VR-based training compared to traditional methods. By examining the current state of the field, this review seeks to identify gaps, challenges, and opportunities for further research and implementation of VR in endoscopic training. METHODS The study is a systematic review, following the guidelines for reporting systematic reviews set out by the PRISMA statement. A comprehensive search command was designed and implemented and run in September 2023 to identify relevant studies available, from electronic databases such as PubMed, Scopus, Cochrane, and Google Scholar. The results were systematically reviewed. RESULTS Sixteen articles were included in the final analysis. The total number of participants was 523. Five studies focused on both upper endoscopy and colonoscopy training, two on upper endoscopy training only, eight on colonoscopy training only, and one on sigmoidoscopy training only. Gastrointestinal Mentor virtual endoscopy simulator was commonly used. Fifteen reported positive results, indicating that VR-based training was feasible and acceptable for endoscopy learners. VR technology helped the trainees enhance their skills in manipulating the endoscope, reducing the procedure time or increasing the technical accuracy, in VR scenarios and real patients. Some studies show that the patient discomfort level decreased significantly. However, some studies show there were no significant differences in patient discomfort and pain scores between VR group and other groups. CONCLUSION VR training is effective for endoscopy training. There are several well-designed randomized controlled trials with large sample sizes, proving the potential of this innovative tool. Thus, VR should be more widely adopted in endoscopy training. Furthermore, combining VR training with conventional methods could be a promising approach that should be implemented in training.

Current status of pediatric radiology in India: a perspective.

This review is a bird's eye view of the practice of pediatric radiology in India. The key focus of this article is training, certification and employment opportunities for radiologists aspiring to specialise in pediatric radiology. Further, we have traced the growth in academic and research opportunities over the past two decades, as well as given a peep into the future trajectory of this speciality. An understanding of these concepts is key to the expansion of pediatric radiologists not just within India, but across the globe.

A Survey of Data-Driven Soft Sensing in Ironmaking System: Research Status and Opportunities.

Data-driven soft sensing modeling is becoming a powerful tool in the ironmaking process due to the rapid development of machine learning and data mining. Although various soft sensing techniques have been successfully used in both the sintering process and blast furnace, they have not been comprehensively reviewed. In this work, we provide an overview of recent advances on soft sensing in the ironmaking process, with a special focus on data-driven techniques. First, we present a general soft sensing development framework of the ironmaking process based on the mechanism analysis and process characteristics. Second, we provide a detailed taxonomy of current soft sensing methods categorized by their predictive tasks (i.e., quality indicators prediction, state parameters prediction, etc.). Finally, we outline several insightful and promising directions, such as self-supervised learning and digital twins in the ironmaking process, for future research.