Identification Of Opportunities Research Articles

Circular supply chain and circular practices: An analysis from the perspective of sustainability and Industry 4.0

AbstractThe objective of the study was to analyse how the integration of Industry 4.0 technologies can promote circular practices within supply chains, aiming for efficiency, transparency and sustainability. The theoretical framework of the research included concepts from Industry 4.0, sustainability, circular supply chains and emerging technologies, underpinning the analysis of the integration of these elements. The research was conducted through a systematic literature review, analysing 28 articles published between 2017 and 2024 that discussed the integration of Industry 4.0 technologies into circular supply chains. The results indicate that the integration of Industry 4.0 technologies predominantly occurs through the paradox of economic growth, efficiency, and technological innovation. This integration aids in promoting circular practices by identifying waste, opportunities for material reuse, tracking waste and by‐products and predicting product demand with greater accuracy, among other benefits. The conclusion of the research highlights the importance of sustainability, innovation and interdisciplinary collaboration in driving more efficient and sustainable practices within supply chains. The contributions include the expansion of knowledge on the integration of Industry 4.0 technologies into circular supply chains, the identification of opportunities for future research, the encouragement of interdisciplinarity and collaboration, and the promotion of more efficient and sustainable practices across various sectors of the economy.

Developing innovative financial products for sustainable economic growth

In today’s competitive landscape, technology firms increasingly turn to advanced data analytics as a strategic tool for boosting revenue growth and operational efficiency. This review explores how leveraging sophisticated analytical techniques can enable these organizations to extract actionable insights from vast datasets, thereby enhancing decision-making processes and driving business performance. Advanced data analytics encompasses a range of methodologies, including predictive analytics, machine learning, and big data analysis, which collectively empower firms to identify trends, optimize resources, and tailor products to meet evolving customer demands. One of the primary benefits of utilizing advanced data analytics is the ability to enhance revenue growth through improved customer targeting and segmentation. By analyzing customer behaviors and preferences, technology firms can develop personalized marketing strategies that resonate with their target audiences, resulting in increased conversion rates and customer loyalty. Moreover, data analytics facilitates the identification of new market opportunities, enabling firms to innovate and expand their product offerings effectively. Operational efficiency is another critical area where advanced data analytics proves invaluable. By monitoring key performance indicators (KPIs) and operational metrics, technology firms can streamline their processes, reduce costs, and minimize waste. Predictive analytics, in particular, allows organizations to anticipate potential disruptions in their operations, enabling proactive measures to mitigate risks and maintain smooth workflows. This capability not only enhances productivity but also fosters a culture of continuous improvement. Additionally, advanced data analytics supports informed strategic planning by providing insights into market dynamics and competitive positioning. Firms can leverage these insights to make data-driven decisions, allocate resources effectively, and align their business strategies with market trends. In conclusion, advanced data analytics serves as a catalyst for revenue growth and operational efficiency in technology firms. By embracing these analytical techniques, organizations can harness the power of data to drive innovation, improve customer engagement, and achieve sustainable competitive advantage. As technology continues to evolve, the strategic implementation of advanced data analytics will be essential for firms seeking to thrive in an increasingly data-driven world. Keywords: Advanced Data Analytics, Revenue Growth, Operational Efficiency, Technology Firms, Predictive Analytics, Customer Targeting, Strategic Planning.

Meeting the accreditation standard through implementation of a multiprogram residency advisory committee and ongoing quality improvement.

In an effort to expedite the publication of articles, AJHP is posting manuscripts online as soon as possible after acceptance. Accepted manuscripts have been peer-reviewed and copyedited, but are posted online before technical formatting and author proofing. These manuscripts are not the final version of record and will be replaced with the final article (formatted per AJHP style and proofed by the authors) at a later time. To describe the process utilized by a large multiprogram residency site to expand preceptor engagement and establish ongoing quality improvement efforts in order to meet the program's needs in response to evolving ASHP accreditation standards. A multiprogram residency advisory committee (RAC) primarily composed of residency program leadership was formed to focus on aspects of program management and accreditation compliance that were not being addressed at the monthly all-preceptor meeting. The ASHP standard and a recent residency accreditation survey guided the RAC agenda, which led to the creation of a combined manual for the institution's 5 residency programs and a preceptor manual. Preceptor engagement was improved through the establishment of local preceptor requirements, inclusion of preceptor representatives on the RAC, expansion of subcommittee opportunities, addition of a preceptor midpoint retreat, and optimization of the end-of-year preceptor retreat. Communication with residents and identification of continual improvement opportunities were improved through roundtables with residents, residency program directors, and the RAC chair; a monthly meeting with the rotating chief resident and RAC chair; and face-to-face exit interviews with the department's chief of pharmacy. The RAC chair has been a key figure in coordinating program change to meet the ASHP standard as well as leading planning for subsequent ASHP surveys. Through the establishment of a multiprogram RAC and a RAC chair, our program has been able to engage a large preceptor group that is dedicated to continual improvement and provides the ability to dynamically respond to ASHP's progressing guidance for pharmacy residency programs.

Cardiac Amyloidosis in Venezuela: A Pending Issue.

Cardiac amyloidosis (CA) is an infiltrative disease characterized by the deposition of misfolded proteins in cardiac interstitial tissue. Interest towards studying this pathology has been growing in the last decade, as new epidemiological insights have revealed that it is not as uncommon as previously believed. Likewise, advances in non-invasive diagnostic approaches and the identification of molecules that modify its long-term progression, even in terms of mortality, have also bolstered interest in CA. Despite this global panorama, in Venezuela, limitations remain regarding the diagnosis of CA, partly associated with a lack of knowledge of the disease. Therefore, additional efforts are necessary for clinical cardiologists to hone their diagnostic skills regarding this disease, as opportune identification is an essential step for its effective management.

Characterization of a deep-water turbiditic reservoir under an active hydrodynamic regime (Niger Delta).

The Egina Field, situated in the deep-water region of the eastern Niger Delta, is characterized by a NE-SW trending anticline that contains several Middle to Upper Miocene stacked reservoirs. Notably, one of the reservoirs in the field includes three sandy intervals, which have been identified as deep marine turbidite systems. The lowest level (Interval 1) comprises a lobe complex, while the uppermost Intervals 2 and 3 consist of erosive channel complexes. These three reservoir intervals exhibit both static and partial dynamic communication. The Egina Field is affected by a coherent network of extensional and oblique-slip faults, with current activity confined to the eastern sector of the structure. Large displacement faults (throw >30m) offset individual reservoir intervals, creating lateral disconnection and acting as barriers to fluid flow across faults. Minor NNE-SSW oriented faults can locally baffle the flow of fluids, as evidenced by well tests and 4D seismic data. Nonetheless, well interference tests suggest good communication within the reservoir. Vertical communication between the stacked sand bodies is facilitated through erosional contacts between reservoir intervals, while lateral communication occurs around segmented faults, via relay ramps and fault tips, in a NE-SW direction. Across the field, ten oil-water contacts have been identified, with a general trend of deepening towards the south. This pattern has been interpreted as a tilted contact caused by an active hydrodynamic regime, where aquifer overpressures gradually decrease from north to south (31 m of difference), aligning with the regional trend. This paper describes how the geological (structural and sedimentological) heterogeneities are paramount in deep-water turbiditic reservoirs, for both static and dynamic conditions. The work presented here shows how the geological analysis can impact reservoir management, driving strategic decisions on field development, as such as the identification of infill wells opportunities or the optimizing the placement of injectors wells, to effectively support producers.

An iterative model for the development of an urban development strategy – a case study of Polanica-Zdrój (Poland)

Motives: The current approach to the design of public space in cities is changing due to the global situation, i.e., the climate and health crisis, as manifested by the COVID 2019 pandemic. There is a need to develop and apply new, innovative research methods and techniques that allow both an in-depth knowledge of a given area and the monitoring of the changes that occur in this area. One of the proposals for such a framework is an iterative model based on the results of the analyses carried out during the research and design work using the research through design (RtD) method.Aim: The aim of this study was to determine the applicability of the iterative process model for the development of urban strategy, particularly in terms of designing more resilient urban public spaces.Results: The iterative process model was tested during consultation meetings on the development strategy for the municipality of Polanica-Zdrój. The design concepts developed during the research were an excellent support for illustrating the goals of the spatial policy of the municipality of Polanica-Zdrój as specified in the draft of its development strategy. They became the starting point for the future design process. A project with blue-green infrastructure (BGI) elements was included in the draft development strategy as an exemplary project for the development and modernization of tourism and tourism-related infrastructure of a supra-local, infrastructural and linear nature. A study using the RtD method supported the identification of opportunities and limitations associated with the implementation of BGI in the protected urban areas.

Simulation Exercise: Learning Entrepreneurship Through Local Market Business Opportunity Identification

This simulation exercise offers transformative experiential learning in entrepreneurship. Integrated with the knowledge, skills and attitudes framework, this exercise immerses students in real-world scenarios of local livelihood businesses. Through hands-on engagement, students propose solutions, fostering critical thinking and problem-solving aligned with Bloom’s Taxonomy. The exercise yields profound experiential learning outcomes, empowering students with insights, skills and attitudes vital for entrepreneurial success.

Explanation of the Opportunity Identification Model Based on Gender Restrictions Affecting Women's Entrepreneurial Identity

Background: Stereotypical beliefs and gender biases play a limiting and discouraging role in the development of women's entrepreneurship, which can have a significant impact on women's willingness to become entrepreneurs. Methods: This research aims to identify and analyze the gender-based limitations affecting the entrepreneurial opportunities of female entrepreneurs using a mixed-methods approach. This research is applied in terms of its objective. In the qualitative phase, 14 experts were selected using a purposeful sampling method. Data collection was conducted through library studies and semi-structured interviews. In this section, the data were analyzed in three stages: open, axial, and selective coding, which resulted in the identification of 51 indicators and 12 components. The research questionnaire was designed based on these indicators. In the quantitative section, the statistical population was all female entrepreneurs in the pharmaceutical companies under study, which totaled 425 people. Using Cochran's formula and a simple random sampling method, 170 people were selected as the sample size. Data collection was carried out using a researcher-made questionnaire, whose reliability was confirmed with a Cronbach's alpha coefficient of 0.89 and validity using expert opinion. Data analysis was performed using SPSS23 and PLS3 Smart software. Results: Based on the research findings, 12 components of social, cultural, economic, educational, legal, behavioral, personality, individual, commercialization, knowledge enhancement, entrepreneurial awareness, and market recognition limitations were identified under the title of dimensions and components of gender-based limitations affecting women's entrepreneurial opportunities. The results also showed that social limitations (β=-0/578), cultural limitations (β=-0/429), economic limitations (β=-0/408), educational limitations (β=-0/346), legal limitations (β=-0/297), behavioral limitations (β=-0/215), personality limitations (β=-0/189), and individual limitations (β=-0/138) have a negative and significant impact on entrepreneurial opportunities

What is the carbon footprint of academic clinical trials? A study of hotspots in 10 trials

BackgroundClinical trials are fundamental to healthcare, however, they also contribute to anthropogenic climate change. Following previous work to develop and test a method and guidance to calculate the carbon footprint...

B-138 A Harmonization Program Leading to Improved Accuracy and Precision of Hemoglobin A1c (HbA1c) Testing: A Six-Year Multi-Site, Multi-Instrument Review and Comparison

Abstract Background Across four global laboratory locations in North America, Europe, and Asia a quality control system was implemented in the measurement of Hemoglobin A1c (HbA1c). The intent was to improve accuracy and reduce imprecision, both being independent contributors to total analytical performance. Methods Quality control (QC) data, created during routine clinical operations, was used for this analysis. Analysis of QC data evaluated bias and precision separately and provided the ability to predict and monitor performance. The in-process harmonization program indicated a change in instrumentation was needed to meet and maintain a more stringent analytical error profile. The instrumentation change allowed for a before and after comparison across platforms. Results Use of a harmonized quality control system allowed for the visualization of the role bias and precision play in measurements. Improved performance was confirmed using native matrix samples tested routinely from participation in the National Glycohemoglobin Standardization Program. Independently assessing bias and precision highlighted the cumulative and offsetting effects that challenge quality assessment and risk mitigation. Bias appeared to have both a transient and systematic nature. The transient bias contributed to the overall normal distributive property of the quality data. In contrast, the systematic accumulation of bias appeared to occur slowly, over multiple reagent and calibration cycles. The accumulation of bias occurred in the direction of the assay drift. While precision commonly consumes the largest amount of analytical error within an instrument, the dual (negative and positive) nature of bias similarly affects the harmonization of an instrument group. Conclusions Changing the way data is viewed to include assessments of bias improved performance and aided in the identification of opportunities to reduce analytical variances that results in inter- and intra-individual variation. Harmonization of instruments should include methods to assess and describe bias, independent of precision.

Energy audit based identification of energy efficiency improvement opportunities for existing houses

Energy efficiency in the building has two dimensions; efficient use of energy resources and energy conservation. Energy-efficient houses play a critical role in energy conservation and achieving sustainable built environment goals. The energy efficiency of a house depends on its building envelope (design, orientation, and energy properties of construction material) and operational characteristics appliance efficiency, energy consumption patterns). Rather than merely ensuring new houses are energy-efficient, it is vital to energy retrofit existing houses. Energy audits can assist in evaluating the energy efficiency of existing houses and identify improvement measures. The main objectives of this study were to identify efficiency improvement opportunities through an energy audit of houses and apartments in Karachi. A detailed energy audit checklist was prepared using literature, standards, expert review, and code requirements. Data was collected through physical and owner-assisted virtual audits of 58 houses in six districts of Karachi. Architectural plans, information about doors, windows, air ducts, thermal images, historical data, and material properties were collected. Audit tools included; an anemometer and thermal imagining camera during physical audits. Android applications were used during owner-assisted audits. Data were analyzed for developing descriptive graphs, U and R-values, Pareto charts, and district-wise mapping of energy properties of the material. As a result, energy improvement opportunities were proposed. These are focused on building envelope aspects, including; window orientation, minimizing air infiltration, and using heatresistant paint. Improvement measures were confirmed through thermal imaging of selected buildings.

Mergers and Acquisitions in the Digital Age: The Role of Technology in Streamlining Financial Integration

Abstract: This comprehensive article explores the transformative role of technology in streamlining financial integration during mergers and acquisitions (M&A) in the digital age. It examines how advanced technological solutions, including cloud-based Enterprise Resource Planning (ERP) systems, automated reconciliation tools, and artificial intelligence (AI) and machine learning (ML) applications, are revolutionizing traditional M&A processes. The paper delves into the impact of these technologies on consolidating financial data, enabling real-time analysis, reducing manual errors, and providing predictive insights for risk assessment and opportunity identification. It also discusses best practices for successful financial integration, emphasizing the importance of pre-merger due diligence, phased integration approaches, and robust cybersecurity measures. Furthermore, the article investigates emerging trends and future prospects in technology-driven M&A, including the potential of blockchain, advanced analytics, and quantum computing to further enhance integration processes. Drawing on recent research and industry surveys, this study highlights the critical role of technology in realizing M&A potential, improving deal outcomes, and creating strategic value in an increasingly complex business environment. The findings underscore the necessity for organizations to embrace technological advancements to remain competitive in the evolving landscape of corporate mergers and acquisitions.

Environmental uncertainty and entrepreneurial orientation in collectivist and individualist cultures: evidence from Brazil and Belgium

ABSTRACT A fundamental premise of the information processing approach in entrepreneurship theory is that the distribution and processing of information is key to opportunity identification. We propose that collectivist-individualist cultural values influence the efficacy of information processing leading to different levels of entrepreneurial orientation (EO). Specifically, we submit that collectivism enhances shared information processing and goal setting in a dynamic environment, while individualism facilitates creativity and divergent thinking that can help EO if sufficient informational input is available. To empirically verify our theory, we study the relationships using survey and archival data from a sample of 487 firms in six industries in Brazil and Belgium, two countries that contrast in collectivism-individualism. Consistent with our predictions, we find higher EO in the collectivist culture of Brazil under high environmental dynamism and low information availability, and this difference is increased by strategic planning.

Harnessing the Power of AI in Salesforce: An Empirical Study on Enhanced Data Insights and Organizational Efficiency

Abstract: This article examines the integration of Artificial Intelligence (AI) in Salesforce platforms to enhance business analytics and decision-making processes. We explore how AI-powered solutions are revolutionizing data analysis, providing organizations with actionable insights, and improving market responsiveness. The article investigates key AI techniques implemented in Salesforce, including machine learning algorithms for pattern recognition and natural language processing for unstructured data analysis. We analyze the impact of these technologies on identifying trends, forecasting, threat detection, and opportunity identification for sustainable growth. Through case studies and empirical analysis, we demonstrate the effectiveness of AI-driven Salesforce solutions in streamlining data processing, enabling real-time market adaptation, and enhancing organizational efficiency. The article also addresses the technological infrastructure supporting these AI solutions, discussing cloud-based computing resources, integration challenges, and data security considerations. Our findings suggest that AIpowered Salesforce solutions significantly improve business analytics capabilities, allowing companies to make more informed decisions and maintain a competitive edge in rapidly evolving markets. This article contributes to the growing body of knowledge on AI applications in customer relationship management and business intelligence systems

Generative Artificial Intelligence Systems and the Challenges in Latin American Education

This article examines the transformative role of Generative Artificial Intelligence (GAI) in education, exploring diverse disciplines such as engineering, medicine, programming, and information systems. GAI emerges as a revolutionary force, promising to fundamentally change educational practices. The PRISMA 2020 methodology (Page et al., 2021) was used to evaluate the relevant scientific literature. The systematic review identified research that applied specific criteria in the analysis of IAG in education. The selected papers covered a variety of disciplines, providing a comprehensive view of the impact of IAG in education. The results show a diversity of approaches and institutional responses to IAG in education. From significant changes in teaching practices to the identification of specific opportunities in disciplines such as computer science and engineering, GAI stands out as a catalyst for transformation. The adaptation of tertiary education, the need for specific skills to work with GAI, and ethical responses emerge as key themes. It focuses on the need for a deeper and more consensual understanding of the role of GAI in education. Concrete research-supported opportunities are highlighted, but ethical limitations and concerns are also underscored. Collaboration, reflection, and adaptation to open educational practices are proposed as approaches to address the challenges and fully exploit the benefits of IAG in education. This comprehensive analysis contributes to understanding the current and future landscape of GAI in education, providing valuable guidelines for educators, institutions, and educational technology developers.

Nested case control study of prevalence and aetiology of dementia in a rural Ugandan population, and a situational analysis of services available for affected families: a protocol. Part of the DEPEND Uganda study (Dementia EPidemiology, unmet Need and co-Developing Solutions).

The prevalence of dementia in low- and middle-income countries is increasing, yet epidemiological data from African populations remain scarce. Crucial risk factors differ in Africa from more intensively studied global areas, including a high burden of cerebrovascular disease and HIV, but lower rates of other risk factors like physical inactivity.Understanding dementia aetiology in African settings has been limited by the expensive and invasive nature of biomarker testing. This study leverages developments in blood-based and retinal imaging biomarker technology to examine the drivers of dementia in older Ugandans.People with dementia have complex needs benefiting from multi-dimensional support. Understanding current services will allow identification of barriers and opportunities to strengthen support available to people with dementia and their families. The study is nested within the existing General Population Cohort run by the MRC/UVRI & LSHTM Research Unit. Currently, all adults aged 60+ (around 1400) are undergoing brief cognitive screening.In Part 1, cohort participants will be selected based on cognitive screening scores to undergo detailed cognitive assessment, using methods developed by the 10/66 Dementia Research Group. Part 2 is a case control study of people with and without dementia using antecedent data, questionnaires, physical assessment, retinal imaging, and Alzheimer's blood-based biomarkers. We will also compare disability, frailty, quality of life, and social engagement in people with and without dementia.Part 3 assesses current provision of formal support for people with dementia through review of publicly available literature and expert interviews. This is the first study in Africa using blood-based and retinal imaging biomarkers to examine the pathological processes underlying dementia, and it will systematically map services available for people with dementia. This paves the way for effective policy strategies for both dementia prevention and support for people with dementia and their families.

Identification of Opportunities for Capitalizing on Tourist Potential in Hunedoara County through Rural Tourism Activities and Supporting the Development of the Local Community

The need to diversify economic activities in rural areas is essential for stimulating sustainable development. In this regard, rural tourism can be an effective tool for supporting the development in rural areas. The purpose of this article was to identify the favorability of Hunedoara County for rural tourism activities, which would contribute to the sustainable development of tourism. Rural tourism activities would generate economic and social benefits both for local communities and for tourists, and at the same time preserve and protect the cultural and natural values of the area. The research methods used to carry out this study are both qualitative (documentary study) and quantitative (a questionnaire applied in order to identify the perceptions of tourists with respect to the tourist development potential of Hunedoara County through rural tourism). The main results of the research consist in the identification of some directions for future development of Hunedoara County. These directions would, in the future, lead to an increase in the visibility of local rural communities; to the preservation of local traditions and customs, while promoting sustainability and respect for the environment; and to the implementation of a plan for sustainable development through rural tourism in the studied area.

Legal education and artificial intelligence: vectors of interaction

Objective: to develop proposals for the introduction of artificial intelligence (AI) in legal education. Methods: dialectical methods (analysis and synthesis, induction and deduction, systematization, comparison, classification, forecasting), statistical, formal-legal and comparative-legal methods. Used in combination, these methods allow comprehensive analysis of the relationship between AI and legal education. Results: the article reveals the main directions to improve legal education in the conditions of AI development: integration of information and communication technologies and training of specialists able to work effectively at the intersection of law and technology. The advantages and disadvantages of using AI in legal education are identified. Ethical aspects of AI application are outlined, as well as the need to manage the development of technologies based on the principles of fairness, transparency and consideration of human interests. The author states the importance of developing not only specialized knowledge, but also universal competencies that will help students to adapt successfully to the dynamically changing conditions of professional activity. Scientific novelty: a comprehensive analysis of the interaction between legal education and AI was carried out, including the identification of specific opportunities for the AI application in legal education, as well as related risks and problems. The author proposes a systematic approach to improving legal education in the context of AI development, focusing on theneed to revise educational programs in legal areas in terms of integrating information and communication technologies; developing universal competencies in students to adapt to a dynamically changing professional environment; introducing mandatory advanced training for judges, legal practitioners to develop skills for using AI systems. Practical significance: the study results can be used to optimize and adapt the educational programs of law schools to the digital era requirements and to develop effective approaches to the AI application in legal practice and education, taking into account ethical aspects and potential risks.

Strategic maintenance planning in the digital era: a hybrid approach merging Reliability-Centered Maintenance with digitalization opportunities

AbstractIn the age of digital transformation, maintenance operations are crucial for leveraging the potential of Industry 4.0 and 5.0. Yet, this domain remains significantly under-optimized in terms of strategic maintenance planning and enhancing asset performance. The advent of smart technologies offers a myriad of innovative avenues; however, harnessing these effectively requires systematic planning that incorporates these new, various and quite diversified, smart practices. Thus, this paper proposes a new methodological approach to maintenance planning, based on the Reliability-Centered Maintenance method, aimed at providing an operative tool for organizations to foster the evolution of their maintenance plans towards the paradigm of digitalization. This novel method enables the identification of hidden opportunities of improvement not identifiable through the use of the traditional approach through the proposal of an Opportunity Index, to use together with the Criticality Index in asset selection, and a Digitalization Score to use during Failure Mode, Effects, and Criticality Analysis. The proposed method is applied to transform the maintenance planning of a production line, thus identifying the opportunities of the approach and testing its feasibility.

Exploring the Formation of Sustainable Entrepreneurial Intentions among Chinese University Students: A Dual Path Moderated Mediation Model

As Sustainable Development Goals (SDGs) gain traction in Chinese society, fostering sustainable entrepreneurship among university students has emerged as a key priority for universities and governments. Methods for increasing students’ sustainable entrepreneurship skills and knowledge for the creation of sustainable startups have attracted substantial attention. This study constructs a moderated mediation model based on entrepreneurial cognition theory to investigate the mediating roles of opportunity identification and attitude in the relationship between sustainable entrepreneurship education and sustainable entrepreneurial intention among university students, in addition to the moderating effect of empathy. The study surveyed 307 students from universities in the Yangtze River Delta region and employed hierarchical regression analysis to test the hypotheses. The results indicate that sustainable entrepreneurship education enhances students’ sustainable entrepreneurial intention by fostering their opportunity identification and attitude, and this enhancement effect is stronger when their level of empathy is higher. These findings enrich entrepreneurial cognition and empathy theories within the context of sustainable entrepreneurship and offer valuable insights for universities and policymakers in developing strategies to support sustainable entrepreneurship among university students.