External Evaluation Research Articles

The Challenge of Social Integration: Enhancing Employability in Work Integration Social Enterprises in Spain

Purpose: Work Integration Social Enterprises (WISEs) are a profitable social initiative as a business. However, there are no studies that analyze their effectiveness. The aim was to assess the effectiveness of the support and guidance processes implemented within WISEs. We hypothesized that insertion workers will perceive improvements at the personal employability dimensions as protective behaviors and a decrease at the employment risks or lack of self-control dimensions. Methods: This study assesses the effectiveness of intervention and training processes across three phases of a training program among 225 insertion workers from 46 WISEs in Spain. Results: Significant improvements in employability factors perceived by both insertion workers and external evaluators were observed across the three evaluation moments, including improved job protection behaviors ( p = .01), reduced employment risk ( p = .03), or reduced barriers to job search ( p = .01). Conclusions: Suggestions for optimizing program effectiveness include tailored training itineraries, continuous monitoring, and promoting soft skills.

The influence of students' linguistic condition, school level, and pedagogical input on analytical essay features

IntroductionAnalytical essays are a fundamental discourse practice within educational settings. These essays are topic-oriented texts that aim to inform readers about a specific matter while persuading them of the writer's perspective. This study investigates how students' linguistic condition (monolingual vs. bilingual) affects their ability to meet the social and discursive expectations of analytical essays. This is examined both over a broad developmental span, from elementary to higher education, and microdevelopmentally, through a sequence of genre-oriented classroom activities.MethodsA corpus of 1,179 essays, written by Spanish monolingual and Catalan/Spanish bilingual students across elementary, secondary, and university levels, was analyzed. Participants were tasked with producing texts on both same and different topics. The analysis focused on lexical, syntactic-discursive and structural features identified as indicators of writing proficiency in the Developing Analytical Writing (DAW) model developed in previous studies. Pedagogical input was controlled by the researchers, and an external evaluation of text quality was performed by teachers from the different school levels.ResultsResults indicate that students' linguistic condition influenced most, but not all, the linguistic and structural indicators of writing proficiency but always in interaction with age/school level and pedagogical input. Improvements were observed across school levels and with pedagogical input. Additionally, teachers varied in their appreciation of different facets of writing performance as a function of the participants' age/school level and pedagogical input. However, the linguistic condition of students alone did not significantly impact external evaluations of text quality.DiscussionOur findings reveal a complex interplay between factors such as writers' linguistic condition, their age/school level, and pedagogical input, which jointly shape the quality of analytical essays.

Evaluation of joint external evaluation to COVID-19 and other infectious diseases mortality outcomes in 96 countries

Abstract Background This study evaluated the effectiveness of Joint External Evaluation (JEE) scores with regard to coronavirus disease 2019 (COVID-19) and other infectious diseases performance in 96 countries. To propose a revised JEE tool, potential JEE indicators were also examined. Methods JEE data from 2016–2019 were linked with outcomes such as COVID-19 fatality rates and infections, as well as mortality rates for other infectious diseases. We also examined potential indicators such as the Sustainable Development Goals (SDGs) and Universal Health Coverage index to propose enhancements to the JEE tool. Multiple regression analysis was used to assess these associations. Results The average JEE score was 2.70 (SD=0.92) in 96 countries. Detection capabilities received the highest average score (3.23), while the other areas (2.30) section received the lowest scores. However, the analysis revealed that the JEE tool had limited predictive accuracy for COVID-19 outcomes. By contrast, the JEE scores showed a negative association with the performance of other infectious diseases. Notably, SDGs 2 (zero hunger), 4 (quality education) and 8 (decent work and economic growth) were strongly associated with better COVID-19 outcomes. Conclusion The JEE scores showed limited predictive value for COVID-19 mortality outcomes in 96 countries. The tool offers insights into health security, but needs revision to better handle future pandemics.

Pursuing the impossible (?) dream: Incorporating attitudes into practice-ready travel demand forecasting models

Despite the fact that our existing models are not up to the job of predicting travel behavior in today’s rapidly changing landscape, and despite considerable evidence that attitudes help us explain behavior more completely and more meaningfully, attitudes are nowhere to be found in practice-oriented travel demand forecasting models. Two main objections have been raised to their inclusion: they are too cumbersome to measure, and difficult-if-not-impossible to forecast. This paper reports on the considerable progress that has been made toward overcoming the first objection, through the use of machine learning methods to train a prediction function on smaller-scale research-oriented survey datasets, and then applying that function to impute attitudes into large-scale household travel survey datasets. Internal evaluations show that we can estimate attitudinal factor scores with moderate fidelity when using socioeconomic/demographic, land use, and targeted marketing variables, and with high fidelity when using just a few attitudinal marker variables. External evaluations demonstrate that the imputed attitudes lead to improved behavioral insight and predictive ability for forecasting-oriented models. With respect to the second objection I have only sketched some ideas for moving forward, but there are clearly some practical steps that could be taken at very little marginal cost, such as including as few as 10 attitudinal marker statements in future household travel surveys.

PERCEIVED STRATEGIES FOR ENHANCING QUALITY ASSURANCE ON SECONDARY SCHOOL PHYSICS TEACHERS IN KOGI EAST EDUCATIONAL ZONE

Quality assurance entails the systematic review of educational provision to maintain and improve its quality, equity and efficiency. It involves self-evaluation, external evaluation, staff evaluation, student evaluation and school evaluation. The purpose of the study was to investigate strategies for enhancing quality assurance in physics education in Kogi East Educational Zone. The study adopted descriptive survey research design. The population for the study comprised all the physics teachers in Kogi East. The sample size for the study consisted of 120 physics teachers which were selected from private and public co-educational secondary schools in the study area using random sampling technique. Two research questions and two hypotheses guided the study. The instrument used for collection of data was a structured questionnaire, titled: Physics Education Quality Assurance Questionnaire (PEQAQ), which was developed by the researcher and validated by experts. The reliability index of the instrument using Cronbach Alpha yielded 0.69. The data collected were analyzed using descriptive and inferential statistics. Findings revealed among others that ensuring functional quality assurance mechanisms in secondary schools in Kogi East provided positive feedback to educational management to enhance performance. Based on the findings, the following recommendation was made. Develop and implement targeted professional development programmes in Kogi State, focusing on research-based quality assurance, strategies and contextualized to address local challenges and needs.

Structure shielding of school and gymnasium buildings against fallout gamma radiation from the Fukushima Daiichi Nuclear Power Plant accident

The radiation dose reduction factor represents a building’s shielding capability against radiation in scenarios of potential nuclear accidents. Notably, the radiation dose reduction for school buildings and gymnasiums have not yet been determined, even though the building types are planned to be used as evaluation shelters in Japan. This study evaluated dose reduction factors in relation to the accident at the Fukushima Daiichi Nuclear Power Plant (FDNPP). In this study, we separately measured the indoor and outdoor ambient dose equivalent rates and the dose rates from natural radionuclides at two school sites in an evacuation-order-lifted area in Fukushima Prefecture, Japan, to evaluate the dose reduction factors of the school buildings and gymnasiums. The factors depended not only on the structure and materials of the buildings, but also on the geographical characteristics of the building locations, which could govern the geometries of irradiation. We noted a non-negligible overestimation of the dose reduction factors by the conventional method, due to the presence of natural radiation in areas with low dose rates (<1 μSv/h). Note that the dose reduction factor is used as an uncertainty source for external dose evaluation related to the FDNPP accident. This study can serve as a foundation for future investigations on improving the resilience of buildings confronted by artificial radiation due to scenarios of nuclear plant accidents.

Degradation of the Antibiotic Sulfamethoxazole by Ozonation: A Comprehensive Review

ABSTRACTSulfamethoxazole (SMX) is an antibiotic widely used for the treatment of several diseases, especially respiratory and urinary. Due to its widespread use, its presence in the environment has been on the rise. This study discusses the degradation of the antibiotic SMX through the ozonation process. SMX is preferentially degraded by the direct action of O3 on the molecule, starting by breaking the double bonds in the aromatic ring. Through ozonation it is possible to obtain complete SMX degradation within 10 min, but the mineralization of the solution is not achieved, reaching total organic carbon removal efficiencies of 5%–60%, depending on the reaction time. Factors such as the presence of organic matter (OM) and the pH of the solution interfere with the degradation of SMX. The OM acts as a radical scavenger, decreasing the efficiency of degradation, while the pH interferes with the decomposition of O3 into radicals and the dissolution of the oxidant in the medium, in addition to influencing the state of ionization of the SMX making it more or less prone to reactions. In general, most other remediation processes are carried out on a laboratory scale. To increase the level of these processes to a full scale, more pilot‐scale studies are needed. In addition, it is necessary to focus on the practice of reusing materials, avoiding the generation of secondary pollution, and increasing the useful life of the material. The review also discusses the reaction mechanisms, intermediate compounds formed, mineralization of the solution, and factors that influence the process, which can help in making decisions for future studies to be carried out in the area. Prospects in the research area revolve around using metal–organic frameworks as molecular imprinting technology to modify heterogeneous catalysts, integration of external energy, bimetallic systems, and evaluation of deactivation mechanisms.

DEVELOPMENT OF MICRO SMALL AND MEDIUM ENTERPRISES IN TOURIST DESTINATIONS AROUND THE NUSANTARA CAPITAL

The East Kalimantan region is a region with rapid development following the designation of the National Capital in one of its regions, namely North Penajam Paser Regency. Therefore, East Kalimantan Province needs to increase MSMEs in tourist destinations as a form of the government's role in optimizing the tourism sector in East Kalimantan. Assuming that the development of the area around IKN will occur rapidly due to the presence of IKN in East Kalimantan, it requires more effective policies to promote the tourism sector. The aim of this research is to collect data on the existing conditions of tourism (tourist destinations) around the IKN area as a forum for developing MSMEs, accommodating the problems of the tourism sector, MSMEs and problems that intersect between these sectors as well as identifying the strengths, weaknesses, opportunities and challenges of MSMEs in tourist destinations around the IKN area, to then provide policy recommendations. This research uses secondary data and primary data. The secondary data used is MSME data which is grouped based on the KBLI classification in the form of business scale; venture capital; business risk; and number of workers. Data collection of information on the existing conditions of MSMEs in tourist destinations around IKN is carried out at the Tourism Office in each Regency/City in East Kalimantan. Analysis of qualitative data was carried out using the SWOT technique. The initial step of SWOT analysis is carried out by determining the internal and external factor matrix. The IFE (Internal Factor Evaluation) and EFE (External Factor Evaluation) matrices consist of columns, weights, ratings and total values which are the result of multiplying the weights and ratings. Ranking of levels of importance is done with the help of the QDA application. The research results show that the condition of MSMEs in tourist destinations around IKN still needs to be improved. This condition is because MSMEs still do not have NIBs, product patents and trademarks, and there are limited human resources for developing digital marketing and financial management. The resulting recommendations are (1) Promotion and innovation of tourist destinations by highlighting superior natural and cultural tourism, (2) Controlling MSMEs related to business licensing, business clustering, and assistance in preparing business financial reports, (3) The government coordinates the use of funds. CSR and other assistance for the development of tourism facilities and MSMEs, as well as (4) Coordination of promotion of local products at tourist destinations as well as training assistance to increase product innovation.

Development and external evaluation of a self-learning auto-segmentation model for Colorectal Cancer Liver Metastases Assessment (COALA)

ObjectivesTotal tumor volume (TTV) is associated with overall and recurrence-free survival in patients with colorectal cancer liver metastases (CRLM). However, the labor-intensive nature of such manual assessments has hampered the clinical adoption of TTV as an imaging biomarker. This study aimed to develop and externally evaluate a CRLM auto-segmentation model on CT scans, to facilitate the clinical adoption of TTV.MethodsWe developed an auto-segmentation model to segment CRLM using 783 contrast-enhanced portal venous phase CTs (CT-PVP) of 373 patients. We used a self-learning setup whereby we first trained a teacher model on 99 manually segmented CT-PVPs from three radiologists. The teacher model was then used to segment CRLM in the remaining 663 CT-PVPs for training the student model. We used the DICE score and the intraclass correlation coefficient (ICC) to compare the student model’s segmentations and the TTV obtained from these segmentations to those obtained from the merged segmentations. We evaluated the student model in an external test set of 50 CT-PVPs from 35 patients from the Oslo University Hospital and an internal test set of 21 CT-PVPs from 10 patients from the Amsterdam University Medical Centers.ResultsThe model reached a mean DICE score of 0.85 (IQR: 0.05) and 0.83 (IQR: 0.10) on the internal and external test sets, respectively. The ICC between the segmented volumes from the student model and from the merged segmentations was 0.97 on both test sets.ConclusionThe developed colorectal cancer liver metastases auto-segmentation model achieved a high DICE score and near-perfect agreement for assessing TTV.Critical relevance statementAI model segments colorectal liver metastases on CT with high performance on two test sets. Accurate segmentation of colorectal liver metastases could facilitate the clinical adoption of total tumor volume as an imaging biomarker for prognosis and treatment response monitoring.Key PointsDeveloped colorectal liver metastases segmentation model to facilitate total tumor volume assessment.Model achieved high performance on internal and external test sets.Model can improve prognostic stratification and treatment planning for colorectal liver metastases.Graphical

A Study on the Factors Influencing Willingness to Use Virtual Reality Systems for External Evaluation of Buildings

A Study on the Factors Influencing Willingness to Use Virtual Reality Systems for External Evaluation of Buildings

Development of Competencies in Emergency Nursing: Comparison Between Self-Assessment and Tutor Evaluation Before and After a Training Intervention.

Nursing competence encompasses the integration of knowledge, skills, and attitudes essential for comprehensive and safe patient care. This study aimed to compare self-assessment and tutor evaluation of nurses' competencies in a hospital emergency department before and after a training intervention. A quasi-experimental design was employed, involving 63 newly hired nurses who participated in a mentorship program. The intervention included theoretical and practical sessions on critical care skills. Data were collected through self-assessment questionnaires and objective evaluations by tutors using validated rubrics. The results indicated significant differences between self-assessment and tutor evaluations in pre- and post-intervention phases, particularly in competencies related to orotracheal intubation and fibrinolytic therapy for ischemic stroke. Post-intervention, discrepancies between self-assessment and tutor evaluations decreased, suggesting improved self-awareness and competence among participants. This study highlights the importance of combining self-assessment and external evaluation to ensure accurate competency assessment and effective educational interventions, ultimately enhancing the quality of patient care.

External evaluation of neonatal vancomycin population pharmacokinetic models: Moving from first-order equations to Bayesian-guided therapeutic monitoring.

Guidelines for vancomycin therapeutic monitoring recommend using a Bayesian approach with a population pharmacokinetic model to estimate the 24 h area under the concentration-time curve over first-order equations. Thus, we performed an external evaluation of population pharmacokinetic models of vancomycin in neonates and compared Bayesian results with those observed in clinical practice via pharmacokinetic equations to improve therapeutic monitoring by proposing optimized initial dosing nomograms and assessing the feasibility of reduced blood sampling strategies using the most predictive models. Models were identified from the literature and evaluated via an external neonatal population. A priori predictive performance was first assessed by prediction-based diagnostics, then by simulation-based diagnostics and a posteriori analyses only if deemed satisfactory; model-informed vancomycin exposure was also compared with reference first-order pharmacokinetic equations. The best-performing models were ultimately subjected to Monte Carlo simulations to develop new initial dosing nomograms offering the highest probability of achieving therapeutic target. A total of 28 population pharmacokinetic models were evaluated in the external dataset, which includes 72 neonates and 380 vancomycin concentrations. Eleven models had an adequate predictive performance with bias ≤ ± 15% and imprecision 30%, while the Bayesian approach yielded over 75% agreement with reference exposure values in most cases. Nonetheless, Capparelli etal. and Mehrotra etal. models performed the best overall, showing the lowest imprecisions of 16.8% and 16.9%, respectively; both models recommended higher dosage regimens than the theoretical nomogram currently applied to favor therapeutic target attainment. We externally evaluated numerous neonatal population pharmacokinetic models of vancomycin and used the most predictive ones to advocate new initial dosing nomograms. Clinical implementation of the Bayesian approach could reduce the time needed to reach therapeutic target and limit the number of blood samples in newborns compared with traditional pharmacokinetic equations.

A Tale of an Airlines Company: Towards A Model of Strategy Formulation Through the Lenses of Sustainable Development Goal

Objective: The purpose of this paper is to explore a few insights into the national airlines of Bangladesh (called Biman) and how they can achieve the Sustainable Development Goals (SDG). Further, the paper evaluates the available strategies using IEF, EFE, SWOT, IE &amp; QSPM matrices/techniques as proposed by David &amp; David (2017). Theoretical Framework: IFE (Internal Factor Evaluation) &amp; EFE (External Factor Evaluation (e.g. input stage), SWOT (Strength, Weakness, Opportunity, and Threats) &amp; IE (Internal and External) matrix (e.g. matching stage), and finally QSPM (Quantitative Strategic Planning Matrix) (e.g. decision-making stage) are used for strategy formulation. Method: This study applies a mixed-method approach. Face-to-face interviews with the passengers of London-Dhaka-London are conducted, and additionally, the content analysis of relevant newspapers and journal articles is carried out. Results and Discussion: QSPM finds, that market development (priority-1), offensive strategy (priority-2), and product development (priority-3) are the appropriate strategies for the airline.It would be not easy to generalize the results as the study is based on one public airline company in a particular country (Bangladesh). Research Implications: This study has both theoretical and practical implications. The study demonstrates how to formulate plans using a quantitative method. The result of this study might be beneficial to Bangladesh's Civil Aviation Authority. The recommendations of this study may help generate profits in Biman. Originality/Value: This study contributes to the strategy literature. Strategy development processes for any business, including aviation, may be eye-opening.

Measured or communicated?

AbstractThis research paper explores the intricate relationship between university rankings, mass democracy, and postmodernity, elucidating the societal shift in evaluating academic excellence. As higher education experiences mass democratization, rankings emerge as vital tools in the new information market, providing accessible metrics for an increasingly diverse audience. The concept of “medialization” underscores the impact of rankings on shaping public perception, as journalists, lacking deep understanding of academic intricacies, turn to rankings for clarity. Reactivity within universities to achieve higher ranking placements underscores the internal influence of external media-driven evaluations. The paper argues that postmodern relativism challenges traditional meritocracy, disrupting the established communicative status of universities. Amidst ongoing debates about the legitimacy of rankings, the research recommends embracing a communicative meritocracy as a strategic response, emphasizing the importance of universities actively shaping their narrative. The emergence of AI, exemplified by chatGPT, is identified as a potential transformative force, offering personalized information and challenging traditional ranking methodologies. The research concludes with a call for continuous self-reflection within ranking systems and universities amidst a changing higher education landscape.

Deep learning-based Covid-19 diagnosis: a thorough assessment with a focus on generalization capabilities

The Covid-19 pandemic has significantly spurred the development of deep learning (DL) models for the pathology automatic diagnosis based on CT scan images. However, the assumption about the generalization of the proposed models remains to be assessed and shown for concrete clinical use. In this work, we have investigated the real value of widely used public datasets for the elaboration of DL models that are dedicated to automatic diagnosis of Covid-19 using CT scans. We have collected various international public datasets from 13 countries. Different Convolutional Neural Networks (CNNs) have been trained and their performances carefully assessed. Two evaluations have been conducted: (1) an internal evaluation following a cross-validation procedure, and (2) an external evaluation on real patients coming from new and different sources. The objective is to assess the generalization capabilities considering real-world conditions: different acquisition conditions, devices and configurations. Three families from the most effective CNN models have been selected (ResNet, DenseNet and EfficientNet). These have been fine-tuned, evaluated and used within a training methodology based on transfer learning. The most effective models have been further customized in order to create new models that are dedicated to the task at hand. These models have significantly improved the diagnosis performance.

External evaluation of intravenous vancomycin population pharmacokinetic models in adults receiving high-flux intermittent haemodialysis.

Patients undergoing haemodialysis (HD) are at greater risk of methicillin-resistant Staphylococcus aureus infections requiring intravenous vancomycin. Close vancomycin therapeutic drug monitoring is warranted in HD patients as renal clearance is the primary elimination pathway. Clinically, population pharmacokinetics (popPK) model-informed dosing is commonly used. This study aimed to perform an external evaluation of published vancomycin popPK models developed for adults undergoing high-flux intermittent HD, and to create a dosing nomogram derived from the model that performed best. A literature review was conducted through PubMed and EMBASE to identify relevant popPK models. an external dataset was collected retrospectively from patients of 2 healthcare centres in Quebec, Canada. Selected models were implemented in NONMEM (v7.5; ICON Development Solutions). Predictive performance was assessed through prediction and simulation-based diagnostics. In total, 2386 vancomycin concentrations were collected from 274 patients and 476 antibiotic courses. Four vancomycin popPK models were selected for evaluation. None of the models demonstrated overall satisfactory or clinically acceptable predictive performance. Nonetheless, Bae et al.'s model performed best with a median prediction error of 16.25% and median absolute prediction error of 34.66%. Different predictive performance was also observed for vancomycin concentrations from samples collected during and between HD sessions. All evaluated models presented poor overall predictive performance. Further studies are required, through existing popPK model parameter re-estimation or new model development, to adequately describe vancomycin pharmacokinetics for our high-flux intermittent HD patient cohort.

Establishing the Institute of Independent Evaluation of Higher Education in the Russian Federation

The paper presents the results of the search, systematization and analysis of independent higher education evaluation systems that have been developed in the country in the recent decade. The research has been carried out using standardised evaluation mechanisms that adhere to the criteria of mass scale, openness, and stability. The analysis of the independent evaluation of higher education’s present situation revealed certain inconsistencies between the legislative and regulatory framework and real practice. It should be emphasised that, while different processes have now been developed for this type of evaluation, they still require enhancement. The assessment mechanisms themselves need to undergo an external, independent evaluation to ensure their reliability, integrity, and trustworthy evidence. It has been indicated that independent evaluation procedures have jointly developed into a system: the institution of independent evaluation. This system is characterised by integrity, orderliness, and definite linkages. One may consider the aggregating technology of the aforementioned evalu-ations to be the synergistic outcome of the system’s establishment. In order to achieve a synergistic effect on the evaluation of all higher education institutions and educational programmes in the country, the authors suggest a method for aggregating the outcomes of the described evaluation procedures. The obtained research outcomes prove their applicability to the internal and external evaluation of a higher education institution’s performance and to the strategic planning of the development of both the institution and the higher education system.

The Health Equity Scholars Program: Fostering Culturally Competent and Successful Independent Investigators in Alzheimer's Disease and Related Dementia Research.

The Health Equity Scholars Program (HESP) addresses the critical need for a diverse, culturally competent workforce to study and treat older adults from underrepresented populations (URPs) with Alzheimer's disease and related dementias (AD/ADRD). The HESP offers tailored mentored training in AD/ADRD research concepts, aiming to develop successful independent researchers. It recruits Scholars from underrepresented backgrounds as well as those passionate about AD/ADRD health equity research. We (1) describe the fundamental elements of the HESP, and (2) present preliminary data from the HESP program evaluation results performed by an outside agency, pre-post participation surveys, and Scholar accomplishments. The HESP Scholars reported high rates of proficiency, satisfaction, and competency in nearly all evaluated areas, and have been successful in obtaining grants, promotions, and publications. These initial outcomes data suggest that the HESP is meeting its objective of diversifying the workforce in the field of AD/ADRD research and care. The Health Equity Scholars Program aims to cultivate a diverse and culturally competent workforce, who are well-prepared to study and treat underrepresented older adults with Alzheimer's disease and related dementias (AD/ADRD). The program provides tailored mentored training in AD/ADRD research concepts, with the goal of nurturing successful independent researchers. Rigorous evaluation processes for applications ensure the selection of highly qualified Scholars. The program includes tailored training activities such as seminars and grant writing workshops, and tracks Scholar achievements while undergoing annual external evaluation to enhance its training program iteratively.

Masculinities in a feminist pedagogy: lessons for transformative gender and agriculture training.

Masculinities and femininities are closely interconnected with men and women farmers' everyday lives; hence critical reflection on these interconnections should be central in gender training in agriculture. While a focus on men and masculinities is crucial for sustainable transformation of deep-rooted gender norms and practices that limit the attainment of gender equality, there are insufficient empirically tested pedagogical models for this purpose. We share a case study, the Gender Responsive Researchers Equipped for Agricultural Transformation (GREAT) model, which incorporates masculinities in a feminist pedagogy. We use external monitoring, evaluation, and learning data for two case study courses that integrate gender in plant breeding, seed systems, and agronomy to demonstrate the efficacy of integrating the concept of masculinity and reflections on male farmers' expectations, behaviors, and practices within a feminist approach to gender training. We conclude that feminist pedagogical practices offer insights into how gender training can integrate a masculinities perspective to move beyond divisive and narrow gender polarities towards addressing masculine norms that often hinder the attainment of gender transformation.

PENYUSUNAN STRATEGI UNTUK MENINGKATKAN BRAND AWARENESS PADA PT PRIORITAS INTI SEJAHTERA MENGGUNAKAN ANALISIS SWOT

Seeks to improve brand recognition among the company's B2B partners to support future market expansion. This qualitative descriptive research, conducted from February to June 2024, comprises 89 pages, excluding appendices. Utilizing the 7P Marketing Mix framework, the research assesses the company’s internal and external environments, resulting in Internal Factor Evaluation (IFE) and External Factor Evaluation (EFE) scores of 5.53403537 and 6.2229091116, respectively. The analysis positions the company in Quadrant 1, indicative of a Growth Oriented Strategy. This strategy recommends an assertive implementation of the 7P Marketing Mix components. The SO strategy harnesses strengths and opportunities, the ST strategy employs strengths to counter threats, the WO strategy exploits opportunities to address weaknesses, and the WT strategy aims to mitigate weaknesses and avert threats. The findings indicate that PT Prioritas Inti Sejahtera’s brand awareness is relatively low, attributed to its recent market entry. This is evidenced by the lower number of application downloads and active users compared to competitors. Therefore, a Growth Oriented Strategy is proposed to increase brand awareness.