Relevant Criteria Research Articles

Teaching methodologies in calculus for engineering: a quantitative analysis

This research quantitatively analyzes worldwide university studies on teaching Differential and Integral Calculus, comparing them with the challenging Brazilian context, which historically faces high rates of failure. Following a Systematic Literature Review structure, 122 documents from different databases (Capes, Scopus, Web of Science, and Science Direct) were reviewed. The focus was placed on worldwide teaching methods for differential and integral calculus, with defined filters and inclusion/exclusion criteria for relevance. According to the results, there is a global rise in alternative and active teaching and learning methods usage. Thus, technological advancements in calculus education through software and group work are highlighted as other means to establish a more student-centric and achievement-oriented learning process. Despite the global progress in teaching calculus, the comparison with Brazil reveals the need to enhance teaching methodologies in national institutions, given the limited number of published studies exploring alternative teaching approaches.

Categorisation of social media influencers and determinants of their engagement effectiveness

Social media influencers have been a topic of interest for both practitioners and scientific community in recent years. Understanding their importance and explaining the mechanisms contributing to their success requires a multidisciplinary approach, incorporating insights from the fields of psychology, media, and economics. This paper explores the current classification of social media influencers based on various relevant criteria as content type, influence type, and followers’ count. Furthermore, this study aims to provide a synthesis of the fragmented findings related to the key determinants of their engagement effectiveness in order to understand the complexity of influencer culture and its implications for marketing science and consumer behavior.

Risk assessment of poverty-returning based on hybrid q-rung orthopair fuzzy EDAS and prospect theory

PurposeAccurately identifying the risk of poverty-returning is a complex and critical challenge in current poverty alleviation efforts. However, there is currently no study on evaluation methods for the risk of poverty-returning. This study aims to establish a robust and systematic approach for an evaluation framework for the risk of poverty-returning.Design/methodology/approachBased on relevant assessment criteria, a maximum deviation method was established to identify the weights of the indicators. A complex evaluation methodology using prospect theory (PT), a q-rung orthopair fuzzy set (QrOFS) and evaluation relying on distance from average solution [EDAS] (QrOFS-PT-EDAS) was developed to evaluate the poverty-returning risks. Some policy recommendations to reduce the risk of poverty-returning have also been put forward.FindingsHis study identifies the risk factors of poverty relapse from nine aspects, including natural disasters, accidents and policy-driven poverty relapse. In addressing the evaluation challenge arising from uncertain decision-making, the QrOFS aligns more with people’s thinking habits and expression methods in complex environments. The proposed hybrid evaluation framework accurately measures the poverty-returning risk, which is beneficial for the formulation of policy recommendations.Originality/valueA scientific and comprehensive assessment system index for poverty-returning is constructed. A hybrid QrOFS-PT-EDAS framework is presented to make the evaluation results more scientific and objective. Several strategic recommendations for reducing the poverty-returning risk are presented. This study offers a novel framework for assessing poverty-returning issues that can be extended to many other areas.

On Optimal Currency Areas: Common Shocks Versus Common Persistence of Shocks

ABSTRACTThe Optimal Currency Area (OCA) literature has been focusing on the co‐movement of business cycle shocks as a key policy criterion. We document in a simple Barro–Gordon framework that, in addition to a high correlation of shocks, a common persistence of shocks is a relevant OCA criterion. The model provides a conceptual underpinning for empirical studies that have used the Serial Correlation Common Features (SCCF) test to evaluate common currency areas. We apply the SCCF test to a set of countries that could potentially introduce the Euro and find for the period from 1999 (Q1) to 2019 (Q3) only little evidence that the acceding countries share a common cyclical response pattern with the European Monetary Union (EMU) aggregate.

Analysis of the Selection of Suppliers of Loading and Transportation Equipment in Mining SMEs

Small- and medium-sized enterprise (SME) mining firms contribute to Chile’s economy. However, more support is needed to improve decision-making, mainly in a context where it is necessary for mining to operate sustainably. Loading and transportation are essential unit operations in mining. Solution-focused supplier companies are joining the market, making selection more difficult. This study suggests a hierarchical analytical process-based multi-criteria analysis. Among what stands out are its simplicity and clarity. The Analytic Hierarchy Process (AHP), used in several fields, is a flexible multi-criteria analysis system for complex decision-making. Its development used Expert Choice® software. The results show that the most crucial criterion for selecting loading and transportation equipment suppliers is related to occupational safety and health. The most relevant components are the mortality, accident frequency, and severity rates. Operational indicators are the second most relevant criterion, enabling companies to be more productive and efficient in achieving their objectives. Sensitivity analysis demonstrates that, even with variations in the criterion preferences, the fatality rate remains at the top of the hierarchy, showing the robustness of the model used. Contrary to what might be expected, criteria such as the supplier profile do not stand out among the critical factors for the sector.

NETQUANT2: automated web-based quantification of neutrophil extracellular traps from fluorescence microscopy.

Neutrophil extracellular traps (NETs) are structures that neutrophils form in response to various stimuli, including invading pathogens. NETs are increasingly studied, and their importance has been demonstrated in autoimmunity and infection. However, no consensus has emerged on their quantification, with many studies resorting to manually counting NETs in microscopy images. NETQUANT is a free software for the automated quantification of neutrophil extracellular traps in fluorescence microscopy images. By employing automated image analysis based on biologically relevant criteria for defining NETs, NETQUANT eliminates user bias and reduces analysis time. Despite these advantages, NETQUANT has not reached widespread adoption, partly due to its dependence on proprietary software and challenges associated with local program setup, which has hindered its appeal. Here, we present NETQUANT2, an improved version based on the principles of NETQUANT, released as a web-based software for fast, simple, and unbiased NET quantification from microscopy images. The software guides researchers by displaying relevant morphological data from their sample and allows researchers to interactively configure the analysis, immediately seeing the impact on the result. NETQUANT2 further improves NETQUANT by enabling easy sharing and reusing of configurations and results and enhanced configuration options to handle complex samples better. We believe that the improved accessibility of NETQUANT2 will lead to better reproducibility in NET research and open the field to more researchers while keeping the quality of analysis high.

Robotic-Assisted Medial Unicompartmental Knee Arthroplasty Provides Better FJS-12 Score and Lower Mid-Term Complication Rates Compared to Conventional Implantation: A Systematic Review and Meta-Analysis

Background: Robotic-assisted unicompartmental arthroplasty (rUKA) is gradually gaining more popularity than its conventional counterpart (cUKA). Current studies are highly heterogenic in terms of methodology and the reported results; therefore, establishing the optimal recommendation for patients becomes less straightforward. For this reason, this meta-analysis aims to provide an up-to-date evidence-based analysis on current evidence regarding clinical outcomes and complication rates following rUKA and cUKA. Methods: A meta-analysis was conducted following PRISMA guidelines. Five databases were searched, PubMed via MEDLINE, Epistemonikos, Cochrane Library, Web of Science, and Scopus. The relevant inclusion criteria were as follows: comparative clinical studies in which medial rUKA was compared to medial cUKA (prospective or retrospective designs), (2) human studies, (3) meta-analyses for cross-referencing, and (4) English language. The relevant extracted data were patient demographics, patient-reported outcome measures (PROMs), range of motion, and complications. A random-effects meta-analysis and subgroup analysis were conducted. The results include mean differences (MDs) and odds ratios (ORs), along with 95% confidence intervals (CIs) for continuous and binary variables, respectively. Results: rUKA showed a higher overall FJS-12 score compared to cUKA, with MD = 6.02 (95%CI: −0.07 to 12.1), p = 0.05. At 6 months postoperatively, the MD increased to 10.31 (95%CI: 5.14 to 15.49), p < 0.01. At a minimum 36-month follow-up, cUKA had a higher all-cause revision rate, with OR = 3.31 (95%CI: 1.25 to 8.8), p = 0.02, and at a minimum 60-month follow-up, a higher aseptic loosening rate, with OR = 3.86 (95%CI: 1.51 to 9.91), p < 0.01, compared to rUKA. Conclusions: rUKA provides better FJS-12 results compared to cUKA, as well as lower all-cause revision and aseptic loosening rates at 36- and 60-month follow-up, respectively. However, long-term follow-up is still pending.

Analysis and Validation of the Development of Science Learning Materials Using a Guided Inquiry Model Combined with Carousel Feedback on the Topic of Light Properties

This study aimed to produce valid learning materials on the topic of light properties using the Plomp development model, which consists of five stages: Preliminary Investigation, Design, Realization, Testing, Evaluation, Revision, and Implementation. The model was modified to suit the specific needs of the study. The modification excluded the implementation phase after completing the test, evaluation, and revision stages. The developed learning materials included a Teaching Module based on guided inquiry combined with carousel feedback, Student Worksheets (LKPD), and a Critical Thinking Skills Test. The study focused solely on the validation process, encompassing construct and content validation of the developed materials. The validation was conducted by experts in science education, instructional design, and evaluation measurement. The validation process aimed to ensure that the learning materials met the criteria of validity, relevance, and feasibility for use. Data from the validation process were analyzed descriptively to determine the level of validity of the materials. Based on the validation results, the developed learning materials were declared valid and suitable for classroom use. The final product of this study was a set of learning materials designed not only to support students' understanding of light properties but also to enhance critical thinking skills through the guided inquiry approach and structured feedback. These materials were expected to contribute to improving the quality of science education in schools, particularly in the application of innovative, 21st-century skill-based teaching methods.

Kombinasi Metode AHP dan TOPSIS dalam Pemilihan Bibit Cabai Berdasarkan Kondisi Tanah dan Syarat Tumbuh Tanaman

Selecting plant seeds suitable for environmental conditions is crucial for enhancing agricultural productivity. This research aims to develop an effective approach for selecting chili seeds based on plant growth requirements. The Analytic Hierarchy Process (AHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) methods are employed to address the complexity of multi-criteria decision-making. The first step involves identifying relevant criteria, including soil type, elevation, optimal soil pH, and light intensity. Subsequently, the relative weights of each criterion are determined using the AHP method to consider the significance of each factor in seed selection. Then, utilizing TOPSIS, chili seeds are evaluated based on their relative closeness to the positive ideal solution (seeds with optimal soil conditions and fulfilled plant growth requirements) and the negative ideal solution (seeds with substandard soil conditions and unmet plant growth requirements). The outcome of this research can assist farmers in choosing chili seeds that match soil conditions and plant growth requirements effectively.

Patients' psychosocial attributes and aggressiveness of cancer treatments near the end of life.

While the use of chemotherapy near the end of life (EOL) has been identified as a relevant criterion for assessing quality of cancer care and has been estimated as non-beneficial, a trend of aggressiveness in cancer care during the last period of life remains. Both patients' sociodemographic characteristics and physicians' practice setting are associated with this use. The role of patients' psychosocial characteristics has however been understudied. The objectives were to study oncologists' intention to recommend chemotherapy or therapeutic abstention in an EOL patient's case and to examine the factors associated with this decision. A clinical vignette-based questionnaire survey was conducted. While the case presented to the participating oncologists of a patient with EGFR-mutated lung cancer, progressing after osimertinib, ECOG 3, with leptomeningeal disease (N = 146), was strictly equivalent in terms of medical aspects and age, 4 patients' non-medical characteristics were manipulated: gender, marital status, parenthood, and psychosocial characteristics ("nice" patients, patients "making strong demands," or control patients). 77.4% of the oncologists surveyed stated that they would recommend chemotherapy in this situation. Only scenarios with nice patients or patients making strong demands were associated with less recommendation of chemotherapy (70.8% for the nice/making strong demands scenarios together vs 87.7%, for the control scenario P = .017). Medical oncologists with previous experience of similar cases were also less keen to recommend chemotherapy (73% vs 100%, P = .007). Of the 76.7% of respondents declaring that they would think of other therapeutic options, 49.1% mentioned "other treatments" without mentioning palliative care. Developing physicians' awareness of the psychosocial aspects at stake in their medical decisions in these sensitive situations may improve EOL care.

A Stakeholder-Related Procedure Model for Social Sustainability Assessment

The importance of assessing the sustainability of companies and their activities is increasing. Especially since the implementation of the new Corporate Social Reporting Directive, even more companies are committed to reporting on the impacts of their businesses on sustainability. This is a challenge especially concerning the social dimension of sustainability. Some frameworks present various relevant social criteria that can be used as a basis for assessment. However, these do not provide detailed suggestions for handling the numerous methodological challenges of such a multi-criteria assessment: identification and selection of the relevant stakeholders, categories and indicators to measure the impacts on social sustainability, weighting and aggregation of these criteria, etc. Therefore, this paper contributes to the methodology of social sustainability assessment by presenting a procedure model for this specific assessment task. The novelty of the model results from its foundation by a review of methods for selection, normalisation, weighting and aggregation of social criteria, existing decision theory-based procedure models, as well as a stakeholder-oriented catalogue of criteria. The procedure model is structured hierarchically by subdividing the overall social sustainability-assessment task into different levels: stakeholders, categories, and indicators. Furthermore, appropriate methods are suggested for the single steps of the procedure model.

Novel conditioning and prophylaxis regimens for relapse prevention.

The last 20 years witnessed relevant clinical advancements in the field of hematopoietic cell transplantation (HCT) for leukemia patients. The introduction of novel conditioning regimens, a better prophylaxis and management of graft- versus-host disease, and an ameliorated posttransplant support system improved safety and, therefore, outcomes. On the other hand, leukemia relapse remains the major cause of allogeneic HCT failure. Efforts have been made to understand the mechanisms of leukemia relapse, and new insights that clarify how donor immunity exerts graft-versus- leukemia (GVL) activity are available. Such studies set the base to design novel transplant strategies that can improve disease control. In our review we begin by discussing the most relevant criteria to choose a donor that provides a strong GVL effect. We also report some of the novel conditioning regimens that aim to deliver and extend myeloablation in order to reduce the disease burden at time of graft infusion. Finally, we discuss how the graft can be manipulated to limit the use of immune suppression and ensure potent antileukemic activity.

Challenges and Opportunities of The Circular Economy for Sustainability Based on Reverse Logistics

Goal: This article's main objective is to analyze the trends and challenges associated with the circular economy (CE) and reverse logistics (RL), with an emphasis on RL's role as a fundamental component of the CE. Theoretical framework: The study's theoretical basis focused on the dimensions and analytical categories of the circular economy and reverse logistics as fundamental elements of environmental sustainability. The analysis considered reverse logistics an integral part of the circular economy to identify its challenges and opportunities. Method and material: The method used was bibliographic. Data were collected from the Google Scholar, Elsevier, and Scielo databases to construct answers to three guiding questions related to a) the trends of the circular economy that allow understanding its integrative vision, the role of reverse logistics in the circular economy, and what are the challenges in implementing the circular economy. Twenty-eight articles on CE and 18 on RL were selected. The definition of the sample considered criteria of relevance, timeliness, and academic impact in articles published in the last fifteen years in high-impact journals. Furthermore, the studies were assessed for their thematic relevance, methodological robustness, and contribution to the development of the field of study. The results were generated using semantic and content analyses. Results and Conclusion: The results found were that a) the trends of the circular economy are the regeneration of resources as a central priority, design is now occupying a central place in sustainability, and the change from ownership to performance, which structure the new human mentality; b) the role of reverse logistics in the circular economy is to promote sustainability in business in practice, mainly through legal structuring, as is the case of the National Solid Waste Policy (PNRS); and c) the main challenges in implementing the circular economy are the lack of understanding of its principles and the lack of cooperation between organizations, governments and consumers. Research implications: It is necessary to start legally structuring and practicing reverse logistics now so that the collective mentality can soon collaborate effectively with sustainability. Originality/value: The study shows that the degree of collaboration between governments, organizations, and consumers is crucial for overcoming the challenges and seizing the opportunities of reverse logistics.

SWOT analysis as a tool for selecting text materials for the formation of English communicative competence of students of non-linguistic specialties

The study is devoted to the implementation of SWOT analysis as an auxiliary criterion for the selection of text material in the formation of English communicative competence for students of non-linguistic specialties. The article examines the concept of communicative competence, as a complex phenomenon of students’ availability of appropriate abilities and skills for high-quality foreign language communication. The main groups of criteria for the selection of text material have been outlined, including 1) subject-scientific ones; 2) linguistic stylistic; 3) methodological; 4) person-oriented. The concept of SWOT analysis has been summarized and the components of the matrix of this analysis have been analyzed, namely: the factors of positive influence of the internal environment are – Strengths, the negative factors – Weaknesses, and the factors of external influence are Opportunities, and the negative ones are Threats. The use of SWOT analysis, based on the classic qualitative criteria for text selection has been proposed as follows: Strengths – linguistic stylistic criteria of variety of types and genres and professionally oriented lexical units; Weaknesses – methodological criteria of authenticity, accessibility, adaptability, etc.; Opportunities – subject-scientific criteria of novelty, informational value and the presence of paralinguistic components; Threats are person-oriented criteria of relevance and practical value. An analysis of the English-language text has been carried out according to the proposed SWOT-analysis model and qualitative criteria for the selection of text material have been highlighted as well.

Essential Curriculum Content for Automotive Body Painting at Vocational High Schools: The Delphi Technique

The extensive content of the curriculum at vocational high schools (SMK) that students must master results in graduates not fully mastering their knowledge. Therefore, this study needs to be conducted to analyze the content of the SMK curriculum so that it can be curated into essential materials based on criteria of urgency, continuity, relevance, and applicability in the curriculum of the automotive body painting course at SMK. This research employs a modified Delphi technique in two rounds, involving a panel of experts consisting of 21 practitioners in the field of automotive painting. The questionnaire was developed concerning the objectives of the automotive body painting curriculum, comprising 16 contents evaluated using a four-level Likert scale. Data collection was carried out using Google Forms. Data analysis was conducted using descriptive statistics with the aid of Excel and SPSS release 27. The study results indicate that there are eight highly essential contents out of the 17 in the automotive body painting curriculum. These eight contents are 1) Implementation of procedures for preparing materials and equipment for repairs; 2) Implementation of panel preparation procedures; 3) Application of putty method; 4) Application of sanding method; 5) Application of masking methods; 6) Implementation of metal panel painting procedures; 7) Implementation of plastic panel painting procedures; and 8) Evaluation and resolution of painting failures. Therefore, in implementing the curriculum, teachers can focus on the highly essential materials to enable students to learn more optimally.

Fermatean Fuzzy TOPSIS Method and Its Application in Ranking Business Intelligence-Based Strategies in Smart City Context

With the expansion of smart cities, the use of business intelligence (BI) has emerged as a crucial tool for resource optimization, increasing efficiency, and improving the citizens’ quality of life. BI enables companies to make better strategic decisions by analyzing vast amounts of urban data, helping them remain competitive in the dynamic smart city environment. This study utilizes content analysis and the Fermatean Fuzzy TOPSIS (FF-TOPSIS) method to rank the strategies based on business intelligence in the context of smart city. Initially, relevant criteria were identified through content analysis, and subsequently, five strategies were developed and ranked based on these criteria. The results revealed that the "Development of IOT-enabled smart networks (S2)" ranked highest, as it plays a significant role in optimizing resource management and enhancing urban service performance, thereby contributing greatly to the advancement of smart cities. "Process automation and the deployment of robotic systems (S5)" ranked second, as it enhances efficiency and reduces human errors. "Cloud platform integration for seamless access to data and services (S3)" also proved to be of considerable importance, ranking third, as it provides seamless access to data and services. " Artificial intelligence deployment for predictive analytics and process optimization (S4)" ranked fourth and was vital for predictive analytics and process optimization, while " Big data analytics for smart decision-making (S1)"—despite its importance—ranked fifth. Urban managers should prioritize the development of IOT networks to fully leverage their potential for resource management and efficiency gains. Following this, attention to process automation and AI integration can significantly enhance the quality of life for citizens and reduce urban costs.

Responding to AI

The influence of artificial intelligence “has enormous implications for higher education” (Bearman, Ryan & Ajjawi, 2023, p. 369). Those of us teaching in the higher education sector have felt this profoundly: after the rapid uplift in digital teaching and learning practices in response to COVID 19 we are required, yet again, to respond to a new set of challenges brought about by the impact of AI. As an example, chatbot technology is calling into question the reliability of the traditional essay as a valid assessment tool (Stokel-Walker, 2022), requiring significant critical reflection and reevaluation of assessments from teaching academics to ensure course learning outcomes are met. This presentation outlines how a teaching specialist academic working in an initial teacher education (ITE) programme at a South Australian university carried out one such redesign. The focus of the re-design was a ‘unit/year plan’ assessment task for a final year curriculum specialization topic. The redesign aligned with the two guiding principles from TEQSA’s Assessment reform for the age of artificial intelligence (Lodge et al., 2023). The first of these guiding principles: ‘Assessment and learning experiences equip students to participate in a world where AI is ubiquitous’ (p. 2) points to the importance of educating students around AI use relevant to their learning. The second guiding principle: ‘Forming trustworthy judgements about student learning in a time of AI requires multiple, inclusive and contextualised approaches to assessment’ (p. 3) underscores the ongoing necessity for universities to have effective means by which to measure student learning outcomes, especially in accredited courses. The redesign of the assessment task both acknowledged the potential of AI for use in the professional space, and simultaneously sought to ensure assessment validity through the inclusion of an interview with the pre-service teachers. Overall, the redesign of the assessment task incorporated three components. Firstly, a brief introductory module about discipline-specific uses of AI was incorporated into the online course content. Secondly, pre-service teachers were ‘permitted’ to utilise available AI platforms in the creation of their planning task. Thirdly, the assessment process was adapted to include an oral presentation (Gulikers, Bastiaens & Kirschner, 2004) conducted as a panel interview in which each pre-service teacher could provide evidence of the pedagogical perspectives underpinning their plan and subsequently demonstrate the successful achievement of topic learning outcomes. The purpose of the panel interview was to assist assessors in forming a judgement about pre-service teachers’ pedagogical understanding and application, in line with relevant criteria from Matheis and John’s Comprehensive Authentic Assessment Model (CAAM) (Matheis & John, 2024). Autoethnographic reflections on the first delivery of the redesigned assessment are provided, including alternative approaches for future iterations. The learnings from the teaching initiative outlined in this presentation contribute to the growing discussion about how we can develop the capacity of our pre-service teachers as skilled and critical practitioners who can utilize AI as a valuable tool for their ongoing professional practice.

DESIGN AND SELECTION OF PADDLE MATERIALS FOR HIGH-LEVEL ROWING COMPETITION APPLICATIONS USING MULTI-CRITERIA DECISION ANALYSIS

The study evaluated a variety of material alternatives including wood, bamboo, carbon fiber reinforced polymer (CFRP), and ceramics for use in high-performance paddleboard. The selection process considers factors such as strength, density, cost, and durability with a focus on the most relevant material criteria for the product. The weighted addition method is used to evaluate and rank several alternative materials that have been selected based on these criteria. Wood and bamboo are chosen for their sustainability, CFRP for their superior strength-to-weight ratio, and ceramics for their resistance to extreme conditions. The study found that CFRP had the highest score of around 85.40 due to its superior strength and lightweight. The framework proposed in this study could provide tools for rowing teams to optimize paddle materials so that they offer the potential for increased speed and performance in the competition.

A new AI-assisted data standard accelerates interoperability in biomedical research.

In this paper, we leveraged Large Language Models(LLMs) to accelerate data wrangling and automate labor-intensive aspects of data discovery and harmonization. This work promotes interoperability standards and enhances data discovery, facilitating AI-readiness in biomedical science with the generation of Common Data Elements (CDEs) as key to harmonizing multiple datasets. Thirty-one studies, various ontologies, and medical coding systems served as source material to create CDEs from which available metadata and context was sent as an API request to 4th-generation OpenAI GPT models to populate each metadata field. A human-in-the-loop (HITL) approach was used to assess quality and accuracy of the generated CDEs. To regulate CDE generation, we employed ElasticSearch and HITL to avoid duplicate CDEs and instead, added them as potential aliases for existing CDEs. The generated CDEs are foundational to assess the interoperability potential of datasets by determining how many data set column headers can be correctly mapped to CDEs as well as quantifying compliance with permissible values and data types. Subject matter experts reviewed generated CDEs and determined that 94.0% of generated metadata fields did not require manual revisions. Data tables from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and the Global Parkinson's Genetic Program (GP2) were used as test cases for interoperability assessments. Column headers from all test cases were successfully mapped to generated CDEs at a rate of 32.4% via elastic search.The interoperability score, a metric for dataset compatibility to CDEs and other connected datasets, based on relevant criteria such as data field completeness and compliance with common harmonization standards averaged 53.8 out of 100 for test cases. With this project, we aim to automate the most tedious aspects of data harmonization, enhancing efficiency and scalability in biomedical research while decreasing activation energy for federated research.

Ensuring the performance of external communications: An informal classification of target groups

The increasing influence of the investment community on business sustainability highlights the need for a compre hensive understanding and accurate segmentation of this audience. The research aims to identify consistent criteria for intra group differentiation in the perception of financial reporting information among members of various stakeholder groups in or der to improve the performance of external communications management. Methodologically, the study rests upon stakeholder theory, which is supported by expert assessments, structural-logical analysis, and multidimensional discriminant analysis. The study draws on authentic data of a survey on the quality of corporate reporting information conducted in the fourth quarter of 2020 among 52 representatives of the Russian business. The research identifies motivationally-rooted statistically significant discrepancies in the probability of correlating some survey participants with their functional group formed on a formal basis. We discuss the relevant criteria for an informal division of respondents into groups based on subjective judgments about qualitative characteristics of corporate financial reports. These criteria include variations in estimates of complexity of reporting standards and functionality of cost indicators based on the concept of fair market value. The revealed criteria for motivational and func tional identification within stable subgroups of financial statement users formed within functional groups represents the scien tific novelty of this study. The results contribute to a deeper understanding of the relevant criteria for the group structure of the investment community, which constitutes the target audience for corporate reporting. These findings can be utilized to refine the formal classification of users of reporting information, as well as to adjust other components of corporate management systems with the aim of enhancing the effectiveness of external communications.