Specific Context Research Articles

Global Perspectives on Management Consulting Competitiveness: Analyzing Knowledge Brokers’ Components

Bridging a significant gap in knowledge broker research, this study addresses the challenges and difficulties in demystifying the roles and components of Knowledge Brokers (KBs) within the management consulting context. Despite their recognized importance, the specific functions, and components of KBs in this specific sector context, known for its intensive use of knowledge, have been unexplored. This study aims to narrow the research gap by identifying key components of KB that enable the knowledge brokerage process in management consulting. Utilizing a mixed methods approach with Structural Equation Modeling (SEM) and data collection from various geographies from global perspectives, the research offers an in-depth understanding of KBs in management consulting. The research findings confirm Interpersonal Skills and Cognitive Ability, along with sub-components like Interactive Skill, Motivational Skill, Hybrid & Anomalous, Neutrality, Professional Competence and Experiential Knowledge, as critical to KBs. The findings offer original contributions to theoretical implications by narrowing the research gaps within this specific context. On the practical front, this study provides strategic insights for organizations to significantly enhance sustainable innovation by integrating external knowledge into organizational decision-making processes, which could be extendable to other industries. Furthermore, it suggests the potential to evolve traditional knowledge brokerage into technology-driven platforms and enhance the innovation ecosystem. Finally, the research findings offer the foundations for future studies on similar professional and knowledge-intensive settings, contextual influences of KBs, and the interrelationships among KB components. Doi: 10.28991/ESJ-2024-08-03-014 Full Text: PDF

From perception to prediction: A comparative study of thermal comfort assessment techniques in school facilities

Indoor environmental quality (IEQ) significantly affects learning, health, and productivity in educational buildings, particularly classrooms. Thermal comfort is crucial to IEQ in classrooms, and various approaches have been developed to assess it. This study compares subjective evaluation, fieldwork measurement, and simulation methods in naturally ventilated secondary school classroom environments in Abuja, Nigeria. It evaluates their reliability, validity, advantages, and limitations. In achieving this objective, fieldwork measurements, questionnaire surveys, and building simulations were conducted in 83 classrooms with 2758 respondents. The data were subjected to descriptive and inferential statistical analysis using the analytical software programs SPSS version 23 and Microsoft Excel. The study found that the Actual Mean Vote (AMV) comfort operative temperature for classrooms was 28.7 °C. Findings from the comparative analysis of the methods indicate that the PMV generally overestimates students’ thermal sensation and that the fieldwork measurement Predicted Mean Votes (PMVf) undervalues the neutral temperature by 4.2 °C. In contrast, the computer-simulated Predicted Mean Votes (PMVs) undervalues it by 3.9 °C. The study found that all three methods are valid and reliable, with some advantages and limitations, depending on the assessment’s specific context and goals. The findings provide valuable insights into improving indoor environmental quality and occupant satisfaction in educational buildings, contributing to the discourse on assessing thermal comfort in classrooms and informing the development of more effective assessment methods. The systematic comparison of these methods addresses a notable gap in the literature, providing practical insights to optimize thermal conditions in learning environments.

Systemic inflammatory markers in neoadjuvant pembrolizumab therapy for triple-negative breast cancer: Prognostic insights and nomogram construction.

e12649 Background: Systemic inflammatory markers derived from peripheral blood cells, such as the neutrophils and lymphocytes ratio (NLR), derived neutrophil lymphocyte ratio (dNLR), platelet-lymphocyte ratio (PLR), and lymphocyte–monocyte ratio (LMR), have shown promise as prognostic markers. Currently, neoadjuvant treatment (NACT) for early triple-negative breast cancer (eTNBC) involves the addition of an immune therapy, and little is known about the variation of these markers in this specific context. Methods: This study evaluated two groups who received NACT for eTNBC in a single third-level cancer center. The first received NACT with EC X4 and a weekly paclitaxel regimen, the second pembrolizumab and NACT. A total of 70 patients were included, 37 patients in the pembrolizumab group. NLR was defined as the absolute blood neutrophil count (N) divided by the absolute lymphocyte count (L), dNLR was defined as the N divided by the derived L (absolute leukocyte count — N), PLR was defined as the absolute platelet count divided by the L, LMR was defined as the L divided by the absolute monocyte count. Association between systemic inflammatory markers and pathological complete response (pCR) was analyzed using statistical tests. Inflammatory markers were evaluated at the time of diagnosis, at the time of chemotherapy regimen change, and 1 week before surgery. The χ2 test or Fisher’s exact test was used for correlation and Student’s t-test to compare different groups. Results: The pCR rates were 60,6% in the standard therapy and 77,8% in the pembrolizumab. There were no significant differences in clinical characteristics between the two groups. NLR, dNLR, PLR and LMR at 6 months showed significant differences compared to baseline levels. dNLR in the immunotherapy group, at the end of therapy, showed statistical significance with the Welch Two Sample t-test with p-value = 0.001. Variables were weighted with respect to the type of treatment and the outcome was assessed as pCR. On the basis of these data, a nomogram was constructed to predict the likelihood of achieving pCR in patients undergoing neoadjuvant pembrolizumab therapy. Conclusions: This study highlights the potential of systemic inflammatory markers as prognostic indicators in patients with eTNBC undergoing NACT. dNLR is a novel biomarker associated with clinical outcome in solid tumors. In this study, for the first time, a correlation was found between the use of pembrolizumab and the change in dNLR and consequently its impact on pCR. A nomogram was constructed to predict the outcome of pCR. [Table: see text]

Global geologic expert system and database for predicting carbonate reservoirs from seismic: Application to the Upper Jurassic

Carbonate systems are influenced by a great variety of physical and biological controlling factors that operate from global to local scales. The resulting intrinsic complexity of carbonate platforms makes them difficult to predict, especially when data are limited. Predicting geologic geometries and properties based on limited sampling or uncalibrated seismic data generally relies on a priori knowledge and equivocal interpretations that are marked by geologist perception and personal experience. To overcome these uncertain interpretations of such a complex natural system, which can become critical in frontier exploration, we developed an expert system that relies on a process-based method and a standardized data set using normalized information and parameters. The main innovation relies on the realization of knowledge- and process-based synthetic carbonate stratigraphic architectures that support seismo-stratigraphic interpretations. The workflow consists of four steps: (1) bibliographic compilation of a geologic database for each case study supported by quantitative parameters (e.g., sedimentation duration and thickness) and qualitative parameters (geodynamic context, seismic architecture, and facies model); (2) statistical analyses to establish consistent geologic classes and spatiotemporal trends; (3) process-based modeling to simulate stratigraphic architectures associated with carbonate sedimentation processes in a physically constrained numerical environment and testing different geologic hypotheses; and (4) realization of a predictive palaeogeographic map representing the global distribution of carbonate stratigraphic architectures, and estimation of controlling parameters for unconstrained case studies. The expert system is based on 77 case studies of Upper Jurassic carbonate platforms, which reveal the resemblance of these carbonate systems, in response to uniform global palaeoclimatic conditions and sea level. Significant local differences in stratigraphic architectures are related to specific geodynamic contexts and subsidence trends. The thickest carbonate platforms are developed in extensive/passive geodynamic settings such as the Central Atlantic Ocean margins, while thinner platforms form in intra- and peri-cratonic settings such as those of the Arabian region.

Introduction: The Writer’s Place

Spatial psychology, a multidisciplinary field combining psychology, neuroscience, and environmental studies, investigates the relationship between individuals and their spatial surroundings (Montello 1998, pg. 143). Grounded in the fundamental notion that cognition is not solely confined to the mind but is intricately intertwined with the spatial environments in which individuals operate, spatial psychology and the psychology of place seek to unravel the cognitive processes, behavioural patterns, and emotional responses that unfold within specific spatial contexts (Poshansky, Fabian, Kaminoff 1983, pg.57). Spatial psychology addresses questions related to how humans perceive, process, and navigate space, encompassing both physical and virtual realms. Informed by spatial psychology, in this special issue we foreground the idea that place is space imbued with meaning, allowing authors the chance to reflect on places of production and to consider (either critically or creatively) the impact of place on their creative ponderings, creative process, and creative products. We asked contributors to consider the following questions: • What are the characteristics of the writer’s (preferred or limited) place of writing, and how important is the articulation/decoration/function of that place in the creative process e.g., the writer’s chair, desk, bookcase, pictures, music, temperature? • What is the writer’s experience – how does the writer ‘feel’ when writing – and how does the place of writing influence that experience, the creative process, and creative outputs; can the place be imagined/ virtual; how does technology affect the planning or design of the writing space; what does the writing in that place smell or taste like? • Does the writer (or their editor?) feel that the work created in a place of the writer’s own making is of a higher quality than if produced in a place they would prefer not to be? • Is the writer’s place only/solely the mind/body, and if so, what goes on in writing in that place?

Analysis of the emotional coloring of text using machine and deep learning methods

The presented scientific article is a comprehensive study of machine learning and deep learning methods in the context of emotion recognition in text data. The main goal of the study is to conduct a comprehensive analysis and comparison of various machine learning and deep learning methods to classify emotions in text. During the work, special attention was paid to the analysis of traditional machine learning algorithms, such as multinomial naive Bayes (MNB), multilayer perceptron (MLP), and support vector machine (SVM), as well as the use of deep learning methods based on long short-term memory (LSTM). The experimental part of the study involves the analysis of different data sets covering a variety of text styles and contexts. The experimental results are analyzed in detail, identifying the advantages and limitations of each method. The article provides practical recommendations for choosing the optimal method depending on the specific tasks and context of the application. The data obtained is important for the development of intelligent systems that can effectively adapt to the emotional aspects of interaction with users. Overall, this work makes a significant contribution to the field of emotion recognition in text and provides a basis for further research in this area.

Harnessing Vietnam's coastal potential: Prioritizing marine energy technologies with an objectively weighting decision-making approach

Vietnam's potential to harness marine energy for sustainable development is significant due to its long coastline, yet this potential remains underutilized as current renewable energy efforts focus mainly on wind and solar power. This study addressed the challenge of selecting optimal Marine Energy Technologies (METs) for Vietnam's specific environmental and socio-economic context. A streamlined methodology, integrating the Method based on the Removal Effects of Criteria (MEREC) and the Spherical Fuzzy Combined Compromise Solution (SF CoCoSo) methods, facilitated a multi-criteria analysis that distilled expert opinions into a decision-making framework. The study identified Point Absorbers (PAB) as the most promising MET for Vietnam, with Overtopping Devices (OTD) and Salinity Gradient Power (SGP) also ranking well based on key factors like readiness and cost. This study introduces a methodology that, with a more comprehensive data set including various marine energy technologies, could provide valuable insights for decision-makers in Vietnam's marine energy sector.

NPV, IRR, PI, PP, and DPP: A unified view

This paper introduces a class of investment project's profitability metrics that includes the net present value (NPV) criterion (which labels a project as weakly profitable if its NPV is nonnegative), internal rate of return (IRR), profitability index (PI), payback period (PP), and discounted payback period (DPP) as special cases. We develop an axiomatic characterization of this class, as well as of the mentioned conventional metrics within the class. The proposed approach offers several key contributions. First, it provides a unified interpretation of profitability metrics as indicators of a project's financial stability across various economic scenarios. Second, it reveals that, except for the NPV criterion, a profitability metric is inherently undefined for some projects. In particular, this implies that any extension of IRR to the space of all projects does not meet a set of reasonable conditions. A similar conclusion is valid for the other mentioned conventional metrics. For each of these metrics, we offer a characterization of the pairs of comparable projects and identify the largest set of projects to which the metric can be unequivocally extended. Third, our study identifies conditions under which the application of one metric is superior to others, helping to guide decision-makers in selecting the most appropriate metric for specific investment contexts.

EEG decoding reveals task-dependent recoding of sensory information in working memory

Working memory (WM) supports future behavior by retaining perceptual information obtained in the recent past. The present study tested the hypothesis that WM recodes sensory information in a format that better supports behavioral goals. We recorded EEG while participants performed color delayed-estimation tasks where the colorwheel for the response was either randomly rotated or held fixed across trials. Accordingly, observers had to remember the exact colors in the Rotation condition, whereas they could prepare for a response based on the fixed mapping between the colors and their corresponding locations on the colorwheel in the No-Rotation condition. Results showed that the color reports were faster and more precise in the No-Rotation condition even when exactly the same set of colors were tested in both conditions. To investigate how the color information was maintained in the brain, we decoded the color using a multivariate EEG classification method. The decoding was limited to the stimulus encoding period in the Rotation condition, whereas it continued to be significant during the maintenance period in the No-Rotation condition, indicating that the color information was actively maintained in the condition. Follow-up analyses suggested that the prolonged decoding was not merely driven by the covert shift of attention but rather by the recoding of sensory information into an action-oriented response format. Together, these results provide converging evidence that WM flexibly recodes sensory information depending on the specific task context to optimize subsequent behavioral performance.

FHIR Implementation Guide for Stroke: A dual focus on the patient’s clinical pathway and value-based healthcare

BackgroundStroke management requires a coordinated strategy, adhering to clinical pathways (CP) and value-based healthcare (VBHC) principles from onset to rehabilitation. However, the discrepancies between these pathways and actual patient experiences highlight the need for ongoing monitoring and addressing interoperability issues across multiple institutions in stroke care. To address this, the Fast Healthcare Interoperability Resource (FHIR) Implementation Guide (IG) standardizes the information exchange among these systems, considering a specific context of use. ObjectiveDevelop an FHIR IG for stroke care rooted in established stroke CP and VBHC principles. MethodWe represented the stroke patient journey by considering the core stroke CP, the International Consortium for Health Outcomes Measurement (ICHOM) dataset for stroke, and a Brazilian case study using the Business Process Model and Notation (BPMN). Next, we developed a data dictionary that aligns variables with existing FHIR resources and adapts profiling from the Brazilian National Health Data Network (BNHDN). ResultsOur BPMN model encompassed three critical phases that represent the entire patient journey from symptom onset to rehabilitation. The stroke data dictionary included 81 variables, which were expressed as questionnaires, profiles, and extensions. The FHIR IG comprised nine pages: Home, Stroke-CP, Data Dictionary, FHIR, ICHOM, Artifacts, Examples, Downloads, and Security. We developed 96 artifacts, including 7 questionnaires, 27 profiles with corresponding example instances, 3 extensions, 18 value sets, and 14 code systems pertinent to ICHOM outcome measures. ConclusionThe FHIR IG for stroke in this study represents a significant advancement in healthcare interoperability, streamlining the tracking of patient outcomes for quality enhancement, facilitating informed treatment choices, and enabling the development of dashboards to promote collaborative excellence in patient care.

Edgar Allan Poe's journey to Russia: fiction and reality

This study highlights the history of E.A. Poe's work on the Russian literary scene, shedding light on the cultural, historical and editorial factors that determined its existence in Russia in the nineteenth century. In analysing the translations, we have resorted to the study of existing studies on the subject, archival materials of the Russian press, literary criticism etc. The aim of the study was to reconstruct the specific context and the specific conditions under which the work of Poe penetrated into Russia, which would also allow us to illustrate the key role of translators in the presentation of Poe on the Russian, French, and world literary scene. The subject of our study was the special conditions that determined the penetration of Poe's work in Russia. The object of the study was the biographies written by different people in different eras, as well as documents that influenced his image. The main method of the study was a comparative analysis of texts that tell about Poe's life and personality. The main result of the research is the reconstruction of the ‘route’, following which Poe's work came to Russia, as well as the identification of all the key persons, without whom Poe's work would have to wait for its time. The article also contributes to our understanding of the historical and cultural context that determined the appearance of Poe on the Russian literary scene, as well as names the most important writers, researchers and translators who paved the way for Poe to come to Russia. Scientific novelty is provided by creating a synthesis of existing studies on this topic in Russian, French and English, which allows to make the most complete three-dimensional picture and chronology of the existence of Poe's work which also provides theoretical significance of the study.

The Effects of Macroeconomic and Financial Development on Income Inequality: Evidence from the Western Balkans

Abstract Using data from 1996 to 2019 covering five Western Balkan countries and applying the linear panel data estimation method, this paper examines the effect of macroeconomic indicators and financial market development on income inequality. Regression results with Driscoll-Kraay standard errors demonstrate that income per capita increases income disparities. Theoretically, there are grounds for both a positive and negative relationship between economic growth and income inequality. In addition, contrary to prevailing literature, our analysis finds no significant impact of financial market development on income inequality, while the rule of law is found to have no effect on income inequalities in these countries. We depart from previous literature by bringing new evidence on the relationship between income inequality and economic growth in the specific context of Western Balkan countries. We study this relationship in an integrated framework and rely on a larger time span, both of which are seemingly important for comprehending the income inequality-economic growth nexus. Certainly, the obtained results bear important policy implications as discussed in this paper.

Analysis of the Communication of Social Responsibility by Energy Companies in Romania

Abstract The awareness towards global changes has increased in recent years and has created pressure for energy providers to improve not only their activity but also the way they communicate their actions, initiatives and commitments and how they report them to the general public. Recognizing this imperative, in January 2022, the European Commission proposed the Corporate Sustainability Reporting Directive (CSRD) to revise and strengthen the existing Non-Financial Reporting Directive (NFRD). With the CSRD's help, sustainability reporting is getting a significant improvement. Now, everything is more transparent and matches up better than other reports created before because it was built around transparency first. This means way less guesswork for anyone needing this information whether it is an investor trying not to worry about their next big decision, consumers, or regulatory bodies. We analyzed the top 15 entities in the electrical energy production sector in Romania, based on their turnover reports at the end of their financial activities for 2022, and we wanted to find out how they articulated and showcased their commitment to social responsibility through their websites and non-financial reports. By examining these reports closely, we uncovered layers of commitment across different sectors from ESG pillars (environmental, social, and governance) – how businesses dedicated to sustainable growth and interacted with stakeholders and by looking closely at these reports, the analysis is not only a point of reference for industry practices but also a better understanding of social responsibility in the specific context of the energy sector.

Hyperparameter Optimization for Impulsive Sound Classifiers

The detection and identification of impulsive sounds applied in a specific context, particularly in sports events, enables the analysis and synthesis of various metrics and statistics associated with the game or even the player's performance. In this context, the automatic identification of an impulsive sound, such as a ball being hit by a player, is a major contribution to the construction of a data source on which game-specific analysis can be performed. Considering all the characteristics (features) of a particular type of impulsive sound in various conditions/environments involves dealing with numerous variables, making it equally challenging to efficiently find the values of the hyperparameters that allow obtaining the best configuration for a given algorithm to be executed in a machine learning process. The contribution of this work is to explore the hyperparameter space in search of values that optimize the performance of the entire process of automatic impulsive sound classification. This process begins with the generation of the dataset to be processed, continues with the training of classification models, and ends with the evaluation of the learned models. The experiments consider a binary classification problem, where a distinction must be made between the intended event and noise. The validation of the process resorts to an audio extracted from videos of sports event competitions, specifically in tennis and padel, where the goal is to identify the sounds of racket hits on the ball. This work is currently in progress, but the preliminary results already enable to evidence the impact of hyperparameter optimization on the accuracy of the overall learning process.

Land use and land cover dynamics in the Upper Ganga Riverine Wetland: unraveling ecosystem services over two decades.

Anthropogenic activities have drastically transformed natural landscapes, profoundly impacting land use and land cover (LULC) and, consequently, the provision and functionality of ecosystem service values (ESVs). Evaluating the changes in LULC and their influence on ESVs is imperative to protect ecologically fragile ecosystems from degradation. This study focuses on a highly sensitive Upper Ganga riverine wetland in India, covering Hapur, Amroha, Bulandshahr, and Sambhal districts, which is well-known for its significant endemic flora and fauna. The study analyzes the subtle variability in ecosystem services offered by the various LULC biomes, including riverine wetland, built-up, cropland, forest, sandbar, and unused land. LULC classification is carried out using Landsat satellite imagery 5 and 8 for the years 2000, 2010, and 2020, using the random forest method. The spatiotemporal changing pattern of ESVs is assessed utilizing the value transfer method with two distinct value coefficients: global value coefficients (C14) for a worldwide perspective and modified local value coefficients X08 for a more specific local context. The results show a significant increase in built-up and unused land, with a corresponding decrease in wetlands and forests from 2000 to 2020. The combined ESVs for all the districts are worth US $5072 million (C14) and US $2139 million (X08) in the year 2000, which declined to US $4510 million (C14) and US $1770 million (X08) in the year 2020. The sensitivity analysis reveals that the coefficient of sensitivity (CS) is below one for all biomes, suggesting the robustness of the employed value coefficients in estimating ESVs. Moreover, the analysis identifies cropland, followed by forests and wetlands, as the LULC biomes most responsive to changes. This research provides crucial insights to stakeholders and policymakers for developing sustainable land management practices aimed at enhancing the ecological worth of the Upper Ganga Riverine Wetland.

La Influencia de la Globalización en la Contabilidad de Costos: Un Enfoque Cualitativo

Globalization has transformed cost accounting, prompting multinational companies to adapt their accounting practices to remain competitive. This study analyzes the influence of globalization through a qualitative literature review. It highlights the implementation of International Financial Reporting Standards (IFRS), the interoperability of globalized accounting systems, and the customization of accounting systems to specific cultural contexts. A comprehensive literature review was conducted, selecting relevant academic articles and case studies. The inclusion criteria covered studies on cost accounting in a context of globalization and the adoption of advanced technologies. The results indicate that IFRS have improved comparability and transparency, although cultural and regulatory challenges remain. The implementation of globalized accounting software, such as ERP systems, has improved financial data management. Companies must invest in advanced technologies, adapt local accounting practices, and understand cultural differences to effectively manage costs and remain competitive.

Crop Recommendation System

Abstract: In the wake of climate change and evolving agricultural practices, there is an increasing demand for innovative technologies to enhance crop productivity while ensuring sustainability. This abstract presents a comprehensive overview of a state-of-the-art Crop Recommendation System (CRS) designed to assist farmers in making informed decisions regarding crop selection. The CRS utilizes machine learning algorithms and data analytics techniques to analyze various factors such as soil type, climate conditions, historical crop performance, market trends, and farmer preferences. Through the integration of satellite imagery, weather data, soil composition analysis, and historical crop yields, the CRS generates personalized recommendations tailored to specific agricultural contexts

Saudi female students’ perceptions of the Community of Inquiry in online learning environments

Distance Education in Saudi Arabia is experiencing a steady increase in female student enrollments due to a number of factors including increased E-learning modalities. E-learning provides more equal learning opportunities than traditional gender-segregated face-to-face classes because online learning environments have fewer gender restrictions. This allows women to participate more equally in higher education and benefit from the expertize of male instructors. This study examines Saudi female students’ perceptions of online learning in university courses taught by male instructors. It documents the supports and challenges female students encountered when they took these courses and considers cognitive, social, and teaching presence. Recommendations include providing faculty training and professional development programs to build online teaching confidence and equip faculty members with teaching skills in culturally specific teaching contexts.

Human-land relationship in the construction of historical settlements based on Complex Adaptive System (CAS) theory: evidence from Shawan in Guangfu region, China

The relationship between humans and land environment within historical settlements reflects the intricate interplay between human societies, their construction activities, and the specific geographical contexts. Inadequate research into this relationship hinders a comprehensive understanding of the social spatial intricacies inherent in historical settlements. This paper adopts the theoretical framework of complex adaptive system and takes Shawan Ancient Town in Guangfu area of China as an example. Under the geographical background of sustainable land growth in the coastal zone, this study analyzed the subtle changes in the relationship between people and land during the historical construction, and the key findings of the investigation are threefold: (1) Land resources play a central role in the construction of human-land relationships in historical settlements. The geographical environment and social institutions serve as configuring factors in the formation and evolution of human-land relationships. These factors collectively determine the formation and evolution of human-land relationships. (2) Social space emerges as a pivotal manifestation of the human–environment relationship in historical settlements, transcending mere physical dimensions. Consequently, a holistic study of this relationship necessitates a comprehensive exploration not only of spatial configurations but also of the intricate interconnections among social bonds, structural formations, societal order, and settlement spatiality. (3) Drawing on the framework of complex adaptive systems theory, the study disentangles intricate elements within the human-land relationship of historical settlements. It distills and examines the manifestations of four intricate adaptive capacities—namely aggregation, non-linearity, flow, and diversity—alongside the mechanisms of tags, internal models, and fundamental building blocks. It is believed that the study of historical settlements in coastal areas needs to grasp the invariable social-spatial objects such as geographical environment, land form, local beliefs. Take it as a clue to sort out how other elements of change have iterated and transformed in the process of historical evolution, such as the rise and fall of families, land ownership changes and social class evolution. This paper explores the value connotation of historical settlements from the perspective of dialectic thinking of change and invariance with CAS theory, which has theoretical significance for protection of settlement's human-land relationship from the perspective of "social-spatial".

The role of comfort, personality, and intention in smartwatch usage during sleep

The comfort of a smartwatch is recognized as a pivotal determinant affecting users’ engagement with the device. This study delved into the intricate interplay between smartwatch comfort, users’ behavioral intention, and their actual usage behavior within the specific context of sleep. Through the lens of a structural equation model, we find that the appearance and movement dimensions of comfort significantly influence users’ intention to wear the smartwatch during sleep, while other dimensions like pressure, harm, attachment, and perceived change do not show significant effects. Furthermore, this intention significantly translated into smartwatch usage behavior. Building on these insights, we subsequently embarked on an exploration of how personality traits interplay with comfort and intention to impact smartwatch usage during sleep. The moderated mediation models revealed that the personality trait of openness acts as a moderator, amplifying the relationship between smartwatch comfort and behavioral intention. Individuals with higher levels of openness exhibit increased inclination to adopt the smartwatch during sleep, even when comfort is compromised. These insights contribute to a nuanced understanding of smartwatch usage behavior and offer guidance for personalized design strategies, especially within the sleep context.