Success Metrics Research Articles

Special issues: The roles of special issues in scholarly communication in a changing publishing landscape

AbstractThis paper aims to enhance the understanding of the role of special issues in the evolving landscape of academic publishing, offering insights for publishers, editors, guest editors, and researchers, including how new technologies influence transparency in publishing processes, open access models, and metrics for success. Based upon original analysis, the paper also discusses the importance of special issues and opportunities to support diversity, equity, and inclusivity in special issue publishing programmes. The goal is to contribute to the discussion of maintaining research integrity through special issues, acknowledging their significance in scholarly communication, while offering suggestions for the future.

The impact of FinTech/Blockchain Adoption on Corporate ESG and DEI Performance

Monitoring a company's efficiency is one of its primary responsibilities. There are many approaches in our contemporary society that either use IT or the conventional technique. Methods for measuring efficiency fall into three primary categories: parametric, nonparametric, and ratio indicators. We prioritize a firm's inputs and outputs when choosing metrics to measure efficiency. Establishing objectives and goals in entrepreneurship necessitates a thorough comprehension, appreciation, and knowledge of sustainability, and assessing the economic growth quality of a corporation is an essential task for theoretical and empirical sustainability assessment. When measuring the efficiency of entrepreneurship in terms of achieving desired values of macroeconomic indicators (e.g., sustainable economic growth objectives), data envelopment analysis (DEA), a widely used technique in efficiency analysis, has taken into account the economic, environmental, and social impact of entrepreneurship as the three dimensions of sustainability. The objective of this paper is to test the influence of FinTech/Blockchain adoption on corporate ESG and DEI performances using a novel DEA approach for sustainable development assessment. It highlights the significance of using a scalable technique for ESG efficiency study and gives scholars a more thorough viewpoint on the subject. In a collection of 50 enterprises, a DEA model was utilized for the analysis. For sustainable performance assessment using the proposed DEA technique, we defined as inputs six financial metrics, and as outputs 11 ESG/Blockchain adoption, and four DEI quality metrics to measure the firm’s efficiency. The annual business data was gathered between 2017 and 2023. In all country situations we discovered that, when DEI initiatives mediate, there is a strong correlation between ESG corporate performance and the quality of economic growth (particularly in the innovation and integrity blockchain adoption performance success metrics). Our study provides additional in-depth details on the FinTech/blockchain adoption environment in comparison to the findings of previous researchers. The sustainable entrepreneurship performance (a latent variable regarded as a dependent target factor) is calculated using eight (8) factors as observed variables, which is the first to consider the dynamics of ESG/BCA and DEI quality metrics as DEA outputs. The study also examines the mediating role of DEI corporate initiatives. By conducting an empirical investigation, the suggested scalable framework makes it evident which company is more efficient in moving toward sustainability, assisting corporate management in increasing the effectiveness of economic growth.

THE POWER OF CONTROL: TRANSFORMING EMPLOYEE ENGAGEMENT IN A POST‐PANDEMIC WORLD

AbstractThe author is a corporate and governmental advisor with a background in executive search and leadership advisory. She points to the changes in workplace motivation: a “list of motivating factors was given to each of us by a high school or college guidance counselor, meant to assist us in plotting out future educational paths based on the career choices expected of us by parents, teachers, friends, and potential employers.” These factors, in her words and further described in the article, are Mission, Leadership, Challenge, Scope of Impact, Acquisition of New Skills, Prestige, Personal Needs, and Money. She contends that “when we use the old metrics of success, and only them in only one order, we mistake filling in checkboxes for what our people really want: consonance.” She describes the latter as “the sense of frictionless belonging, of momentous stride, of core relevance.” The “new definition of success,” is built around, in her words, calling, connection, contribution, and control. Related factors are, in her words, flexible work arrangements, autonomy in task management, involvement in decision making, clear communication and expectations, professional development opportunities, empowering middle management, and leading with inspiration.

Advancing Women Entrepreneurs: A Framework for Small Family Businesses Success within the Sustainable Economy

This article introduces the Holistic Enterprise Success and Sustainability Index (HESSI), a novel framework designed to enhance the success of women-led small family businesses (SFBs) in the context of a sustainable economy. Through a comprehensive literature review and theoretical exploration, this study articulates how women entrepreneurs' perspectives are intricately aligned with both familial values and business imperatives. HESSI employs a robust suite of indicators to measure financial robustness, societal contribution, environmental stewardship, and family solidarity—each meticulously refined to reflect the specificities of women-led SFBs. These indicators transcend traditional, financial-centric metrics, advocating for an expansive evaluation of success that considers economic performance alongside social, environmental, and familial well-being. Crucially, the HESSI framework incorporates women's familial insights, positioning them as a driver of internal cohesion and a pivotal element in integrating Environmental, Social, and Governance (ESG) principles. This broader vision of success metrics includes family unity and the perpetuation of legacy. HESSI promotes an all-encompassing approach to success evaluation that is grounded in gender perspectives, entrepreneurial agility, and a staunch commitment to sustainability principles. The discourse presented is a significant contribution to the fields of gender, entrepreneurship, and sustainable development, providing actionable insights into the vital role of women entrepreneurs in forwarding the sustainability agenda. It underscores the importance of advancing education, reinforcing policy frameworks, and fostering community solidarity to support and extend the reach of women-led SFBs, thus charting a course towards a more equitable and sustainable future in the business landscape.

Education’s primary motive of overall human development in India: Case based perspective of Dayalbagh Educational Institute

The Indian higher education system faces significant challenges in integrating value-based education, sustainability, and consciousness, often prioritizing academic achievements over holistic development. This case-based research explores how Dayalbagh Educational Institute (DEI) effectively addresses these challenges by incorporating sustainability, value, and consciousness into its educational framework. DEI was selected for its distinctive approach, which emphasizes moral and social responsibility, fostering not only academic success but also the ethical development of students. The study draws on document analysis and observations to illustrate how DEI’s educational practices serve as a model for other institutions. The research underscores the urgent need for educational reforms in India that go beyond traditional metrics of success, addressing the gaps in moral education and sustainable practices. By fostering critical thinking, ethical decision-making, and social responsibility, DEI demonstrates how an education system can prepare students for future challenges while promoting a deeper consciousness about their role in society. The findings suggest that integrating value-based education with sustainability and consciousness not only enhances students’ holistic development but also contributes to broader goals of national development. DEI’s model offers practical insights and evidence for other educational institutions to adopt similar strategies, ensuring that future generations are better equipped to address societal challenges with a strong ethical foundation. This research thus provides a comprehensive view of the essential elements needed in modern education to create responsible and conscious global citizens.

Merit-Based Sortition in Decentralized Systems

In decentralized systems, it is often necessary to select an 'active' subset of participants from the total participant pool, with the goal of satisfying computational limitations or optimizing resource efficiency. This selection can sometimes be made at random, mirroring the sortition practice invented in classical antiquity aimed at achieving a high degree of statistical representativeness. However, the recent emergence of specialized decentralized networks that solve concrete coordination problems and are characterized by measurable success metrics often requires prioritizing performance optimization over representativeness. We introduce a simple algorithm for 'merit-based sortition', in which the quality of each participant influences its probability of being drafted into the active set, while simultaneously retaining representativeness by allowing inactive participants an infinite number of chances to be drafted into the active set with non-zero probability. Using a suite of numerical experiments, we demonstrate that our algorithm boosts the quality metric describing the performance of the active set by >2 times the intrinsic stochasticity. This implies that merit-based sortition ensures a statistically significant performance boost to the drafted, 'active' set, while retaining the property of classical, random sortition that it enables upward mobility from a much larger 'inactive' set. This way, merit-based sortition fulfils a key requirement for decentralized systems in need of performance optimization.

Reimagining higher education: The impact of learner outcome metrics in Ireland and beyond

AbstractA college is an institution that exists to provide instruction. Subtly but profoundly, we are shifting to a new paradigm: a college is an institution that exists to produce learning (Barr & Tagg, 1995, p. 13). This paper traces the evolution of learner outcomes, from their progeny as a diagnostic tool in accurately measuring learning gains and facilitating institutional self‐improvement, to their present distorted incarnation, in propagating “governance by numbers”. The paper proceeds in a number of steps. Firstly, it begins with a brief contextualization of the topography of higher education. It then moves to explore the OECD influences regarding quantifying outcomes and aligning them with performance metrics. From here, it looks to EU deliberations in the shape of the Bologna Process with its enduring iterations, the purpose of which benchmarks HEIs' (higher education institutions) success against the successful achievement of learner outcomes. To conclude, taking the example of the Irish funding and strategy, Hunt Report (National Strategy for Higher Education to 2030), I provide an explanatory account detailing how this “learning outcomes race” and its association with “success metrics” within the higher education landscape is mistaken and harmful.

Examining Bald Eagle Contaminant Exposure and Reproductive Risk Above and Below Dams on Great Lakes Tributaries.

Removing lowermost dams can reestablish fish passage on Great Lakes tributaries. This can increase the transfer of contaminants from anadromous fish to piscivorous wildlife upstream; however, concentrations of bioaccumulative contaminants in Great Lakes fish have decreased over the last several decades. We analyzed concentrations of PCBs and the toxic equivalence (TEQs) calculated from PCBs, DDTs, other organochlorine pesticides, and PBDEs in the plasma of bald eagle nestlings above and below lowermost dams on five river systems in Michigan from 1999 to 2013. We examined relationships between contaminants and metrics of reproductive success from 1997 to 2018, including the effects of year and location relative to the lowermost dam. Σ20PCB and p,p'-DDE were important in characterizing differences in contaminant mixtures above and below dams. Concentrations of contaminants were generally greater below dams than above. There were generally greater nest success and more nestlings per nest below dams, but nest location explained little variability (R2 values = 0.03-0.15). Neither Σ20PCB nor p,p'-DDE was a significant predictor of 5-year productivity means by river reach despite concentrations exceeding previously established effects thresholds for healthy bald eagle populations in the Great Lakes (≥ 1 nestling/nest). Our study indicates that dams may continue to reduce the upstream movement of contaminants to bald eagles, but at the measured concentrations, contaminants did not impair productivity and reproductive success as indicated by nestlings per nest. Additional information about population dynamics could clarify population-level effects of contaminants on bald eagles and to what degree these populations are self-sustaining throughout the Great Lakes.

Diverse Metrics of Success for Physician-Scientists: Reflections on My Path and the Evolving Role of NIAID.

Diverse Metrics of Success for Physician-Scientists: Reflections on My Path and the Evolving Role of NIAID.

Using an Ensemble of Segmentation Methods to Detect Vertebral Bodies on Radiographs.

Vertebral compression fractures may indicate osteoporosis but are underdiagnosed and underreported by radiologists. We have developed an ensemble of vertebral body (VB) segmentation models for lateral radiographs as a critical component of an automated, opportunistic screening tool. Our goal is to detect the approximate location of thoracic and lumbar VBs, including fractured vertebra, on lateral radiographs. The Osteoporotic Fractures in Men Study (MrOS) data set includes spine radiographs of 5994 men aged ≥65 years from 6 clinical centers. Two segmentation models, U-Net and Mask-RCNN (Region-based Convolutional Neural Network), were independently trained on the MrOS data set retrospectively, and an ensemble was created by combining them. Primary performance metrics for VB detection success included precision, recall, and F1 score for object detection on a held-out test set. Intersection over union (IoU) and Dice coefficient were also calculated as secondary metrics of performance for the test set. A separate external data set from a quaternary health care enterprise was acquired to test generalizability, comprising diagnostic clinical radiographs from men and women aged ≥65 years. The trained models achieved F1 score of U-Net = 83.42%, Mask-RCNN = 86.30%, and ensemble = 88.34% in detecting all VBs, and F1 score of U-Net = 87.88%, Mask-RCNN = 92.31%, and ensemble = 97.14% in detecting severely fractured vertebrae. The trained models achieved an average IoU per VB of 0.759 for U-Net and 0.709 for Mask-RCNN. The trained models achieved F1 score of U-Net = 81.11%, Mask-RCNN = 79.24%, and ensemble = 87.72% in detecting all VBs in the external data set. An ensemble model combining predictions from U-Net and Mask-RCNN resulted in the best performance in detecting VBs on lateral radiographs and generalized well to an external data set. This model could be a key component of a pipeline to detect fractures on all vertebrae in a radiograph in an automated, opportunistic screening tool under development.

Multiple plant-community traits improve predictions of later-stage outcomes of restoration drill seedings: Implications for metrics of success

Success of ecological restoration is often only knowable if treatments meet criteria defined by biotic thresholds, but analytical frameworks to determine metrics of success and their underlying thresholds are needed. Early indicators of longer-term recovery trajectories are particularly critical where re-treatments may be required, such as in harsh climates or where repeated disturbances or invasive pressures prevail. We developed a framework for identifying which biotic traits would provide the best initial indication of longer-term target restoration goals and applied the framework to restoration drill-seedings of deep-rooted perennial bunchgrasses (DRPBGs) used to rehabilitate and restore semiarid rangelands threatened by exotic annual grasses (EAGs, e.g. cheatgrass) and the recurrent wildfire that EAGs cause. Initial traits measured included cover, basal diameter, height, and density (#plants/area) of DRPBGs and cover of EAGs and Sandberg bluegrass (Poa secunda, POSE, a disturbance-adapted perennial). The longer-term target objective was ≥25 % DRPBG cover and ≤13 % EAG cover by the 5th year following drill-seedings. Measurements were made on 112 plots spanning 113,000 ha in sagebrush steppe on the Soda wildfire scar, in the Northern Great Basin, USA. Traits of DRPBGs tended to be uncorrelated with one another, thus each was informative in describing vegetation condition. Where DRPBG cover was initially >17 %, it tended to become >25 % by the 5th-year post-seeding. In plots that overcame an initial risk of not meeting the target objective (i.e. <17 % initial DRPBG cover), DRPBG tended be large DRPBGs (>22.8 cm height) and plots also had >7 % cover of POSE. Additional “sets” of initial vegetation traits were also predictive of longer-term restoration success or failure. Restoration drill-seeding of DRPBGs is a key but varied-outcome tool for breaking the exotic grass-fire cycle, and, contrary to a conventional tendency to rely on a limited number of mean traits such as % cover, a suite of biotic traits appears necessary to monitor to reliably know if trials are likely to yield success.

Addressing Latinx cancer care equity program for long-term united skills building (ALCANCE-PLUS): Updated results from an ongoing implementation.

151 Background: Addressing Latinx Cancer Care Equity - Program for Long-term United Skills Building (ALCANCE-PLUS) is an ongoing community-academic partnership between the Stanford University School of Medicine Partnerships to Advance Care and Pacific Cancer Care (PCC). The partnership began in 2019 and is comprised of several community-identified multi-level interventions to improve cancer health equity in an undeserved, rural migrant farm-working community. The intervention components are delivered by trained community health workers to low-income and racial and ethnic minoritized patients receiving active cancer treatment and include: 1) precision medicine education using literacy- and language-concordant educational tools; 2) food insecurity screening and intervention with plans to cross-train &gt; 150 CHW's across the county to expand cancer screening and care delivery in the county. Here, we describe the characteristics of participants and the program's impact to date on metrics identified by the community. Methods: ALCANCE-PLUS eligibility includes: all patients with cancer actively receiving cancer-directed treatment at PCC who are ≥ 18 years old and speak English or Spanish. Community identified metrics of success include: % treatment adherence (completion), no-show rate, days from diagnosis to treatment, and % who received clinical trials education as compared to baseline (prior to program start). We used descriptive statistics and chi-squared tests to compare metrics of participants in the program to baseline. Results: At baseline, 62% of low-income and racial and ethnic minoritized patients in the county completed treatment, 35% had no-shows to clinic or infusion appointments with an average of 82.7 days from diagnosis to treatment and only 15% received clinical trial education. From July 2022 to May 2024, a total of 164 patients participated in the program. Mean ages were 60.88 ± 14.55, 68 (41.5%) identified as male, 104 (63.4%) as Hispanic or Latino, 2 (1.2%) African American or Black, 12 (7.3%) Asian American, 2 (1.2%) Native Hawaiian or Other Pacific Islanders, and 60 (36.6%) White. Insurance types included 63 (25.6%) patients with Medicaid, 56 (22.6) with Medicare, 13 (5.2%) with both, 72 (29%) with private insurance, and 7 (2.8%) with other insurance or uninsured. As of January 2024, treatment adherence was 100% for the 157 program participants, the average time from diagnosis to treatment dropped from 82.7 days county-wide pre-program to 30 days among enrolled participants, all participants received clinical trial education, and 38 (24.2%) were actively participating in a clinical trial. Conclusions: Community-academic partnerships to co-design and implement approaches to overcome community-identified needs for marginalized populations are essential to achieve cancer health equity.

Circular economy and critical barriers: Mapping the pathways and success metrics for sustainable circular success in industrialised South Asian developing nations

The economy of a developing country is often industry centric, and is recognised globally. The circular economy (CE) model involves a manufacturing approach where products are systematically remanufactured and recycled within facilities to minimize waste. The emerging domain of CE in industrialised South Asian economies offers considerable benefits for developing countries due to its sustainable production, although its adoption is obstructed by various barriers. This research aims to develop a model for adopting CE within the industrial sector of South Asian developing nations by analysing the interrelation between overcoming circular economy adoption barriers (CEABs) and sustainable circular success (SCS). To attain this, questionnaire was completed by 310 industrial experts in Pakistan. Furthermore, a partial least square structural equation modelling (PLS-SEM) approach was employed to specify the barriers and inspect the interrelation between overcoming CEABs and SCS. The findings revealed a high correlation, with addressing the CEABs contributing 66.1 % to the SCS of the industrial sector. The results of this study indicate the outer loadings and average variance extracted values for all constructs surpassed the minimum threshold of 0.5, validating their acceptance. Moreover, the constructs in the study were measured reliably, exceeding a value of 0.8, which signify strong internal consistency. Additionally, the average path coefficient value (β) of 0.172 indicates a medium and positive correlation between CEABs and SCS. The study's findings can be used as a reference for policymakers to explore the primary barriers to CE adoption in developing nations and achieve SCS in industrial projects.

Fat storage and drought tolerance in a seasonally‐adapted primate: Implications for modeling the effects of animal responses to global climate change

AbstractGlobal warming is changing habitats and affecting biodiversity, and is expected to exacerbate aridification in many regions. Animals and plants in seasonally dry tropical forests often exhibit adaptations to cope with seasonal resource limitation. However, whether these adaptations will facilitate drought tolerance or increase drought vulnerability is unclear. Here, we combine long‐term individual‐based data on phenology, morphometrics, and demographics to investigate how drought impacts the food resources, health, reproduction, and behavior of a population of Verreaux's sifaka (Propithecus verreauxi), a critically endangered lemur inhabiting dry deciduous forests in Madagascar. Between December 2010 and May 2023, the population experienced 3 years of severe drought (2016, 2017, 2022). During green periods in severe drought, the availability of high‐quality sifaka foods (young leaves, fruit) was significantly reduced and fruit tree mortality increased. This reduced availability of fruit persisted in the year after a drought, despite typical rainfall. Yet surprisingly, we found no negative effects on body condition or commonly‐used metrics for reproductive success during drought years or years following a drought. Instead, sifaka exhibited significantly higher levels of subcutaneous body fat during severe droughts. We observed little change in sifaka behavior between drought and non‐drought periods. However, they were more likely to lick dew during severe drought, and spent significantly less time feeding on young and mature leaves. They also significantly increased their time feeding on flowers and fruits, despite the reduced abundance of fruit in the habitat. Together, our results suggest that increased consumption of water‐rich fruit and flowers during severe droughts could facilitate physiological mechanisms that help sifaka cope with water scarcity, including fructose‐mediated fat storage, metabolic water production, and water conservation. These results provide new insights into how critically endangered animals may respond to climate change, suggesting that behavioral and physiological adaptations to seasonal resource limitation may buffer some mammals from the effects of severe drought or other extreme weather events.

Pathways to success: a machine learning approach to predicting investor dynamics in equity and lending crowdfunding campaigns

AbstractCrowdfunding has evolved into a formidable mechanism for collective financing, challenging traditional funding sources such as bank loans, venture capital, and private equity with its global reach and versatile applications across various sectors. This paper explores the complex dynamics of crowdfunding platforms, particularly focusing on investor behaviour and investment patterns within equity and lending campaigns in Italy. By leveraging advanced machine learning techniques, including XGBoost and LSTM networks, we develop predictive models that dynamically analyze real-time and historical data to accurately forecast the success or failure of crowdfunding campaigns. To address the existing gaps in crowdfunding analysis tools, we introduce two novel datasets—one for equity crowdfunding and another for lending. Moreover, our approach extends beyond traditional binary success metrics, proposing novel measures. The insights gained from this study could support crowdfunding strategies, significantly improving project selection and promotional tactics on platforms. By enhancing decision-making processes and providing forward-looking guidance to investors, our computational model aims to empower both campaign creators and platform administrators, ultimately improving the overall efficacy and sustainability of crowdfunding as a financing tool.

226. PHILOSOPHICAL CONSIDERATIONS IN SURGICAL INNOVATION

Abstract Background Innovation in surgery has been viewed as synonymous with progress. This is not always the case as many new innovative processes, devices and techniques do not yield same results in "real world" as they do in the experimental stage. The purpose of this presentation is to discuss the role of philosophical experiment in the process of appraisal of surgical innovation. Methods A thought experiment was conducted analysing past surgical innovations. Introduction of electrosurgery, laparoscopic cholecystectomy, surgical safety checklist and laparoscopic aortic aneurysm repair were tested. All consequences (known and hypothetical) of these innovations were considered in attempt to establish a more holistic metric of success. Results Significant limitations exist in the current assessment methods of innovation "success" which is commonly defined based on the results of a study of chosen pre-set metrics (main outcome). The utility of key metric used to assess innovation (e.g. lengths of hospital stay or visual pain scores) is limited by the choice of these outcomes. This reduces the changes of detecting rate, but possibly, much more significant unintended effects both advantageous and harmful (e.g. discovery of insulin vs thalidomide). The magnitude of detectable change is dictated by practicality of powering controlled studies and exposes results to the sensitivity bias. Unanticipated effects of the innovation are frequently not discovered until it is adopted on a large scale. Various outcomes of innovation are non-commensurable and further complicate the definition of "success". A novel innovation outcome assessment process is proposed: net global utility, a composite outcome measure which considers all potential effects of innovation (clinical, social, economic, ethical and other). Net global utility is a subjective measure that allows observer to compare non-commensurable values by not using them in isolation. One of the main advantages of net global utility is that it only requires knowledge of available metrics and principles of logical argument, providing an easy assessment tool to boost local oversight of introduction of innovation and policy-making. It includes calculation of risk (probability x consequence) which allows to account for improbable but highly consequential outcomes. Net global utility is compared to the best available alternative and derives internal face validity from this. Net global utility encompasses potential incidental future benefits as well as assessment of innovation against the test of justice. Conclusion Defining success in surgical innovation can be challenging. The use of thought experiment and logical argument is described to introduce a novel metric "net global utility" allowing for composite assessment of innovation success. Various previous surgical innovations used to demonstrate the application of the net global utility.

A tool for clarifying expectations in undergraduate research experiences.

Articulating clear and achievable expectations is fundamental to both education and organizational management. In this article, we provide a simple intervention for clarifying expectations-and establishing that these expectations have been understood-which proved beneficial both to community college interns and to their internship mentors in biotech-related undergraduate research experiences. Internship mentors were asked to utilize a simple Expectation Clarity Tool to outline the expectations, success metrics, baseline assessments, and training strategy and support that would be foundational to their intern's project. These included expectations around conceptual, technical, performance, and professional skills and behaviors. Concurrently, but independently, community college interns were asked to complete the same type of exercise as a way of identifying gaps in their knowledge and understanding of their mentor's expectations and their internship project. The mentor's completed Expectation Clarity Tool was then shared with their intern. As a result of completing this relatively simple intervention, the majority of mentors reported that it increased their confidence as a mentor, taught them a new mentoring skill, changed how they will mentor trainees moving forward, and positively impacted their relationship with their trainee. On the intern side, the majority of interns reported that engaging in this intervention, both as an independent exercise and in obtaining their mentor's completed Expectation Clarity Tool, increased their confidence as an intern and positively impacted the success of their internship.

Assessing the impact of corporate governance principles on the Small and Medium Enterprises (SMEs)’ financial success in Kwa-Zulu Natal (KZN): Application of Stewardship theory

This study investigates how corporate governance (CG) principles affect the financial performance of Small and Medium Enterprises (SMEs) in Kwa-Zulu Natal (KZN), South Africa, using stewardship theory. Corporate governance (CG) encompasses the regulations, procedures, and mechanisms Overseeing the administration and implementation of a business. Efficient corporate governance (CG) is crucial for Small and Medium Enterprises (SMEs) to function with maximum effectiveness and optimise entrepreneurial value. The study seeks to fill this vacuum in information by investigating the impact of using stewardship theory, which prioritises the long-term interests of stakeholders, on the financial performance of small and medium-sized enterprises (SMEs) in KZN.A quantitative approach was employed and a cross-sectional design was employed to survey 217 SMEs in the Durban South area. Descriptive statistics reveal a diversified KZN SME environment, with a predominance of medium-sized businesses, balanced gender representation, and a variety of business ages and educational backgrounds among owners and managers. Inferential statistics show significant correlations between CG principles and financial success metrics of SMEs, particularly affecting returns on invested capital and assets, net profit, asset value, and sales turnover. The results are consistent with earlier studies on the beneficial effects of CG on SME performance. The study is limited to SMEs in the Durban South area and may not be generalizable to other regions. Future research might compare studies across different areas and examine the long-term effects of CG on SMEs to identify optimum practices. The study recommends prioritizing efficient CG procedures tailored to SME needs. It suggests developing business management competencies and advocating for supporting legislation to enhance SME performance.

Engineering Features From Advanced Medical Technology Initiative Submissions to Enable Predictive Modeling for Proposal Success.

The U.S. Army Telemedicine and Advanced Technology Research Center Advanced Medical Technology Initiative (AMTI) demonstrate key emerging technologies related to military medicine. AMTI invites researchers to submit proposals for short-term funding opportunities that support this goal. AMTI proposal selection is guided by a time-intensive peer review process, where proposals are rated on innovation, military relevance, metrics for success, and return on investment. Utilizing machine learning (ML) could assist in proposal evaluations by learning relationships between proposal performance and proposal features. This research explores the viability of artificial intelligence/ML for predicting proposal ratings given content-based proposal features. Although not meant to replace experts, a model-based approach to evaluating proposal quality could work alongside experts to provide a fast, minimally biased estimate of proposal performance. This article presents initial stages of a project aiming to use ML to prioritize research proposals. The initial steps included a literature review to identify potential features. Then, these features were extracted from a dataset consisting of past proposals submissions. The dataset includes 824 proposals submitted to the AMTI program from 2010 to 2022. The analysis will inform a discussion of anticipated next steps toward developing a ML model. The following features were created for future modeling: requested funds; word count by section; readability by section; citations and partners identified; and term frequency-inverse document frequency word vectors. This initial process identified the top ranked words (data, health, injury, device, treatment, technology, etc.) among the abstract, problem to be solved, military relevance, and metrics/outcomes text proposal fields. The analysis also evaluated the text fields for readability using the Flesch readability scale. Most proposals text fields were categorized as "college graduate," indicating a challenging readability level. Finally, citations and partners were reviewed as an indicator of proposal successfulness. This research was the first stage of a larger project to explore the use of ML to predict proposal ratings for the purpose of providing automated support to proposal reviewers and to reveal the preferences and values of AMTI proposal reviewers and other decision-makers. The result of this work will provide practical insights regarding the review process for the AMTI program. This will facilitate reduction in bias for AMTI innovators and a streamlined and subjective process for AMTI administrators, which benefits the military health system overall.

Success Metrics of the Ridho Illahi Breeders' Cooperative in Enhancing Welfare in Wanasaba

This study aims to examine the factors that determine the success of breeder cooperatives, particularly in enhancing business competitiveness and the welfare of the breeder community. The research employs a descriptive-qualitative method with Interpretive Structural Modelling (ISM) analysis. Data were collected through interviews and focus group discussions (FGD) with members of the Ridho Illahi Breeders Cooperative in Wanasaba subdistrict, West Nusa Tenggara. The results indicate that several factors contribute to the success of breeder cooperatives, with the technical skills of breeders having the most significant impact. The ISM model highlights that the critical areas of focus for breeder cooperatives should be the operation of upstream and downstream business systems and the marketing strategies for livestock products. The contribution of this research provides valuable insights for breeder cooperative management to enhance business competitiveness. The originality of this study lies in its model used to identify key factors for the success of breeders in improving competitiveness and welfare.