ABSTRACT
BACKGROUND: Conceptual models are abstract representations of the real world. They are used to refine medical and nonmedical health care scopes of service. During the COVID-19 pandemic, numerous analytic predictive models were generated aiming to evaluate the impact of implemented policies on mitigating the spread of the virus. The models also aimed to examine the psychosocial factors that might govern the general population's adherence to these policies and to identify factors that could affect COVID-19 vaccine uptake and allocation. The outcomes of these analytic models helped set priorities when vaccines were available and predicted readiness to resume non-COVID-19 health care services. OBJECTIVE: The objective of our research was to implement a descriptive-analytical conceptual model that analyzes the data of all COVID-19-positive cases admitted to our hospital from March 1 to May 31, 2020, the initial wave of the pandemic, the time interval during which local policies and clinical guidelines were constantly updated to mitigate the local effects of COVID-19, minimize mortality, reduce intensive care unit (ICU) admission, and ensure the safety of health care providers. The primary outcome of interest was to identify factors that might affect mortality and ICU admission rates and the impact of the implemented policy on COVID-19 positivity among health care providers. The secondary outcome of interest was to evaluate the sensitivity of the COVID-19 visual score, implemented by the Saudi Arabia Ministry of Health for COVID-19 risk assessment, and CURB-65 (confusion, urea, respiratory rate, blood pressure, and age >65 years) scores in predicting ICU admission or mortality among the study population. METHODS: This was a cross-sectional study. The relevant attributes were constructed based on research findings from the first wave of the pandemic and were electronically retrieved from the hospital database. Analysis of the conceptual model was based on the International Society for Pharmacoeconomics and Outcomes Research guidelines and the Society for Medical Decision-Making. RESULTS: A total of 275 individuals tested positive for COVID-19 within the study design interval. The conceptualization model revealed a low-risk population based on the following attributes: a mean age of 42 (SD 19.2) years; 19% (51/275) of the study population being older adults ≥60 years of age; 80% (220/275) having a CURB-65 score <4; 53% (147/275) having no comorbidities; 5% (13/275) having extreme obesity; and 20% (55/275) having a significant hematological abnormality. The overall rate of ICU admission for the study population was 5% (13/275), and the overall mortality rate was 1.5% (4/275). The multivariate correlation analysis revealed that a high-selectivity approach was adopted, resulting in patients with complex medical problems not being sent to MOH isolation facilities. Furthermore, 5% of health care providers tested positive for COVID-19, none of whom were health care providers allocated to the COVID-19 screening areas, indicating the effectiveness of the policy implemented to ensure the safety of health care providers. CONCLUSIONS: Based on the conceptual model outcome, the selectivity applied in retaining high-risk populations within the hospital might have contributed to the observed low mortality rate, without increasing the risk to attending health care providers.
ABSTRACT
Shifting to mobile payments from offline payments can be considered as a social distancing measure in times of a pandemic. The COVID-19 outbreak is currently entering its 'endemic' stage;continued usage of mobile-based payment services is thereby warranted as a social distancing mechanism. This could be true in case of any other pandemic/endemic outbreaks like SARS/Nipah virus outbreaks. The current study examines how the 'perceived' health threat posed by COVID-19 and mobile payment service quality (MPSQ) influence consumers' perceived value toward continuous usage of mobile payment services (MPS) in India. In addition, the investigation considers other factors that prompt consumers to continue using the service. Customers, who used mobile payment applications for making cashless transactions during the pandemic, formed the subjects of the study. Data were collected from 720 mobile payment users. The research model integrates the concept of health threat in health belief model to means-end chain model to explain why a customer opts to choose m-payment at times of a pandemic, and what prompts him/her to continue with its usage. The model was empirically tested with structural equation modeling, along with mediation and moderation analysis. It was found that MPSQ, perceived susceptibility, and perceived severity of COVID-19 significantly enhanced consumers' value perceptions regarding MPS, which leads to satisfaction and continuance intention of using the same. In addition, the study also found a significant positive moderating role of consumer involvement on the relationship between perceived health threat, perceived value, and MPSQ. The threat of COVID-19, being an endemic, or occurrence of similar pandemics persists, and adopting contactless transactions via MPS to comply with social distancing norms may improve customer value perceptions that could aid in the persistence of MPS usage. Also, derivation of value perceptions out of the service quality acts as a driver to continuous usage.
ABSTRACT
The key objective of our study involves devising a conceptual model for estimation of social media acceptance by students for effectively accomplishing their educational and academic goals. Factors e.g., perceived social capital, social influence, and perceived mobility that associated with student acceptance of social media were investigated, and integrated into the TAM model using the PLS-SEM. Data were collected through online survey (461 students) at UAE universities. The findings revealed that mentioned factors positively affected students' intention to use social media during their learning process. Respondents' behavioral intention were also linked to both the core and external constructs of the TAM. Important practical insights on technology acceptance in education were provided. © 2022 IEEE.
ABSTRACT
COVID-19 is currently a global pandemic with worldwide magnitude and transversal implications. In Sri Lanka, during several island-wide curfews imposed since March 2020 and up to now, the agriculture industry's stakeholders and consumers have been coming across several challenges such as food scarcity, dramatic price fluctuations of commodities, and difficulties in searching of market for both product buying and selling. Also, communities have faced challenges related to the timely purchase of planting materials and other agro-inputs (fertilizers and pesticides), loss of income, inadequacy of reliable advices and directions, and market uncertainties, which have demoralized them with no clear way forward. This blockage created a sudden imbalance of the entire value chain of agriculture industry affecting almost all stakeholders. Electronic representation of physical entities-such as local fairs and mega trading hubs driven by computer intelligence services-are believed in this study to be viable solutions to overcome most of the above-mentioned challenges. Therefore, this study proposes a smart-agriculture support system naming it as Electronic Partner for Agro Services (EPAS), which would seamlessly connect farmers, consumers, and other relevant stakeholders of the agriculture value chain in the virtual space electronically. The system intends to regulate price for goods and services while organizing a balanced supply and demand in more informative and intelligent manner, thus provisioning electronic financial accounting facilities for subscribers. Timely dissemination of knowledge, advice, financial services and linking agro-input suppliers are also embedded into the proposed model. The Design Science Research (DSR) Methodology was adopted in this study in developing the EPAS conceptual model. © The Author(s), under exclusive license to Springer Nature Switzerland AG 2022. All rights reserved.
ABSTRACT
COVID-19 played a significant role in the spread of telework worldwide, changing people's lives and behaviour. The paper aims to identify how teleworking affected the sustainable behaviour of employees during the COVID-19 pandemic. The research design applies a multi-method approach, combining systematic and comparative scientific literature analysis and a semi-structured interview. The authors of the paper present the theoretical conceptual model, which illustrates links between teleworking during the COVID-19 pandemic and the sustainable behaviour of employees. The results of empirical research revealed that teleworking during the COVID-19 pandemic changed employee behaviour in economic, environmental and social dimensions. Positive changes were identified due to reduced commuting and shopping;decreased costs for transport, food, clothing, and beauty services;better access to healthy and nutritious food;better opportunities for professional development. On the contrary, costs for home energy and household waste increased. Adverse effects on employees' physical and mental health have been identified due to teleworking and COVID-19. Despite the identified negative effects, employees would like to continue teleworking even after the pandemic. © 2023 Ramunė Čiarnienė et al., published by Sciendo.
ABSTRACT
Background: Pharmaceutical businesses had enormous difficulties in product distribution during COVID-19, and the solution to this perpetual issue is a resilient supply chain. Aim(s): The study aims to understand the vulnerabilities to which it subjected the pharmaceutical product distribution supply chains during the COVID-19 pandemic and further develop an adaptive model through which the pharmaceutical product supply chain can enhance its resilience capabilities. Material(s) and Method(s): The conceptual model is developed for the supply chain of pharmaceutical companies based on the literature survey, and then the conceptual model is explored through factor analysis. Researchers have developed a validated model after a statistical analysis using Cronbach's alpha. Subjective analysis has concluded that the pharmaceutical supply chain's resilience is driven by factors such as "trade cost," which comprises transport cost, business practices, and raw material sourcing cost;"shock propagation," which comprises country-specific shocks, production shocks, and policy changes;and "technological infrastructure bottleneck," which relates to the availability of cold chain storage warehouses and refrigerated transport vehicle facilities. Result(s): An empirical model pertaining to supply chain resilience may be further studied with different geographies, like Pune, Hyderabad, and Delhi NCR, for the purpose of generalizing the study. Conclusion(s): The identified major factors were trade cost, shock propagation, and technological infrastructure bottlenecks. The sensitivity of the issue under investigation required a personal touch to the survey, as the COVID-19 pandemic had left these respondents emotionally vulnerable. As COVID-19 is the recent catastrophe that has hit humanity, it has made the pharmaceutical product distribution channel vulnerable during the pandemic. This difficult time of pandemic has really tested the pharmaceutical products' supply chain capabilities as well.Copyright © 2023, Association of Pharmaceutical Teachers of India. All rights reserved.
ABSTRACT
Background: The emergence of implementation science has driven an increase in research examining the implementation of evidence-based programs and policies. However, there has been less attention through program sustainability. To achieve the full benefit of investment in program development and implementation, there must be an understanding of the factors that relate to sustainability; additionally, there is a need for a robust set of tools and trainings to support strategic long-term program sustainability. This paper presents results of our sustainability training intervention and a new conceptual model of sustainability. The proposed conceptual model builds upon the intervention design, further specifying the implementation strategy, strategy-mechanism linkages, and effect modifiers. Methods: This research is part of the larger randomized control trial evaluating the effectiveness of the Program Sustainability Action Planning Model and Training Curricula. Specifically, this multimethod study establishes a conceptual model for program sustainability and related capacity-building interventions. The training intervention was delivered through workshops and technical assistance to 11 state tobacco control programs, principally entailing the development and implementation of a sustainability action plan. We utilize descriptive statistics and participant perspectives to evaluate the training intervention and propose an empirically-grounded conceptual model for sustainability capacity-building interventions in public health settings. Results: Participants found intervention components (workshop, workbook, instructor and resources) to be effective. Overall, participants found the intervention improved their ability to develop sustainability action plans and assess their program and partners. Throughout the study, program managers emphasized the importance of the workshop in providing direction for their sustainability work and the value of robust, ongoing technical assistance. Program managers identified several factors that interfered with intervention reception including staff turnover, competing priorities, partnership challenges, and the COVID-19 pandemic. Conclusion: The present study documents the development and implementation of a novel Program Sustainability Action Planning Model and Training Curricula, one of the first interventions designed to improve program sustainability. In addition, we present an empirically-grounded conceptual model for program sustainability. Considering the paucity of research in this understudied and undefined topic area, this is an important contribution that can serve as a framework for similar intervention designs and implementation efforts. Clinical Trail Registration: ClinicalTrails.gov identification number is NCT03598114.
ABSTRACT
This study aims to examine the suitability of the conceptual model regarding the effect of business strategy, user competence, organizational structure on the Effectiveness of Management Accounting Software (MAS), and how the influence between the variables studied during the Covid 19 Pandemic took place. Quantitative methods are used to test the suitability of the proposed model and to determine the predicted effect between the variables studied. The data were tested using Covarian Base Structural Equation Model (CB-SEM) with Lisrell 8.5 software. This study uses primary data collected through questionnaires to a population of 118 State-Owned Enterprises (SOEs) Management Accounting departments in Indonesia, with a selected sample size of 100 SOEs, which were selected using a simple random technique. The results of this study succeeded in confirming the conceptual model developed by the researcher and empirically proving the influence of business strategy on MAS Effectiveness, user competence on MAS Effectiveness and organizational structure on MAS Effectiveness in Indonesian SOEs companies. The effectiveness of MAS depends on the relevance of the needs of its users. The right business strategy, effectively provides relevant information for the company to design MAIS according to user needs, so that the company's operational activities run effectively and efficiently, the company is able to implement a Cost Reduction Strategy through production cost savings, production process accuracy, implementing product differentiation and low pricing strategy with a focus on customer needs during the Covid-19 pandemic. The results of this study contribute to producing strategic management accounting information to anticipate business continuity during and after the Covid 19 Pandemic and to help overcome the crisis due to the Covid 19 pandemic in the early stages of the Covid 19 Pandemic by optimizing business strategy, organizational structure, and company HR competencies. © 2022 IEEE.
ABSTRACT
This study investigates the role of Knowledge Management (KM) in integrating corporate sustainability practices in the post-pandemic context. It also examines the current literature on KM and sustainable development and develops a sustainable conceptual model. Based on a survey of contemporary literature and KM and corporate sustainability approach, this study proposes a conceptual framework with KM and corporate sustainability strategy as fundamental constructs to attain organisational excellence (OE) in the post-pandemic era. The research adds conceptual and situational elements such as the interaction between KM and sustainability strategy, creative approaches for developing a structural framework, and the right direction for boosting efficiency. The research is one of the first to present a comprehensive framework for achieving OE in the post-pandemic era. Furthermore, by focussing on COVID-19 and the post-pandemic environment, this research provides a new perspective on KM and corporate sustainability literature. © 2023 World Scientific Publishing Co.
ABSTRACT
The COVID-19 pandemic has induced changes in the regular patterns of social interaction, causing the need for new approaches to teaching social work. This work aims to examine the features, opportunities, and prospects of implementing e-learning in Social Work Education. The study recruited 116 students from [anonymized for blind peer review] University and 109 students from [anonymized for blind peer review] University. All participants were asked to complete online questionnaires with the view of assessing their perceptions of e-learning. The study uses a structural analysis of the content of academic research in the field of online education in social work to create a questionnaire for surveying students. Based on the results of the descriptive statistics of a students' survey and the intersection with the study of the corresponding corpus of academic research, a Conceptual model of e-learning in Social Work Education is proposed, which integrates the available academic findings and the real situation estimation in accordance with the assessment of students. Findings suggest that e-learning as a tool for teaching is a promising alternative to traditional classroom or blended learning. The effectiveness of e-learning in social work was highlighted.
ABSTRACT
Systems Thinking can help to solve complex problems in different domains. For an engineering master's program, we designed a seminar course to teach Systems Thinking. For the seminar we use qualitative models known as archetypes as conceptual models and the Covid-19 pandemic as problem context. In this paper we describe the course design and report findings from running it. Based on students' evaluation and the materials they produced throughout the course, our findings (1) support our design assumptions regarding student motivation, (2) give hints on students' struggling with Systems Thinking and understanding and applying archetypes in particular. With this we want to contribute to the discussion of how to teach Systems Thinking in Higher Education. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
Several industry-specific metadata initiatives have historically facilitated structured data modeling for the web in domains such as commerce, publishing, social media, and so forth. The metadata vocabularies produced by these initiatives allow developers to "wrap” information on the web to provide machine-readable signals for search engines, advertisers, and user-facing content on apps and websites, thus assisting with surfacing facts about people, places, and products. A universal iteration of such a project called Schema.org started in 2011, resulting from a partnership between Google, Microsoft, Yahoo, and Yandex to collaborate on a single structured data model across domains. Yet, few studies have explored the metadata vocabulary terms in this significant web resource. What terms are included, upon what subject domains do they focus, and how does Schema.org represent knowledge in its conceptual model? This article presents findings from our extraction and analysis of the documented release history and complete hierarchy on Schema.org's developer pages. We provide a semantic network visualization of Schema.org, including an analysis of its modularity and domains, and discuss its global significance concerning fact-checking and COVID-19. We end by theorizing Schema.org as a gatekeeper of data on the web that authors vocabulary that everyday web users encounter in their searches. © 2023 The Authors. Journal of the Association for Information Science and Technology published by Wiley Periodicals LLC on behalf of Association for Information Science and Technology.
ABSTRACT
A multichannel interaction service is a practice whereby organizations communicate and interact with their existing customers and potential new customers through different channels. This article presents a brief case study of multichannel interaction in healthcare services, which studies the viability of continuous multichannel interaction for personalized healthcare services to enable health professionals to follow up and monitor patients in home-based care. Furthermore, this study aims to explore the possibility of the continuity and complementarity of the interactions across different communication channels with the patients. The data used for this study was gathered during the first wave of the COVID-19 pandemic. This study showed that despite this type of interaction being relatively new in healthcare services, it has considerable potential for improving the relationship between patients, health professionals, and care providers. Upon completion of the data analysis, several conclusions were drawn. One such conclusion was the ability to maintain continuity of interaction across multiple channels, as well as the synergy between the different channels of interaction available to patients and the impact this has on the way patients and health professionals interact. Additionally, it was determined that the complementarity of different interaction channels is crucial when implementing multichannel interaction services. Furthermore, the implementation of this solution resulted in improved communication between patients and health professionals. Also, it has decreased health professional's workload and reduced care providers costs regarding remote patient follow-up. © 2023 by the authors.
ABSTRACT
seeing high-tech medical devices from other nations and witnessing surgery to learn has become nearly unattainable. The pandemic of coronavirus disease 2019 (COVID-19) has created cross-border medical education challenging. Nevertheless, to cater to the increase in non-face-to-face education, instructional techniques entailing the 'metaverse' are being initiated in the medical field, since medical staff from all over the globe who frequented the UAE to acquire skills in medical technology and medical students who require to exercise have already had minimal prospects to collaborate closely with patients attributable to COVID-19. Employing video-conferencing technology like Zoom to provide effective medical education is similarly difficult. The research's goal is to learn the perception of students in the UAE towards the metaverse system (MV) used for medical training. The conceptual model includes The Technology Acceptance Model (TAM) elements and adoption aspects of perceived value. The research's conceptual model, which connects both personal-based traits and technological features, is what makes it novel. Additionally, the novel hybrid analysis approach will be applied in the present research to conduct machine learning (ML) driven structural equation modeling (SEM) evaluation. © 2022 IEEE.
ABSTRACT
Previous studies on remote work have not fully understood which roles are suitable for remote work. In our study, we performed the literature review method and developed a conceptual model inspired by transaction cost theory. Additionally, we believe remote work is an optional option in the context of hybrid work during COVID-19. Our conceptual model leads us to believe that remote workers incur some additional perceived costs in the remote work process. We analyze the following four different roles to understand their perceived costs of working remotely: CEO, product manager, database engineer, and administrative employee. We are expected to provide theoretical explanations for what factors influence remote workers' perceived transaction costs. © 2022 International Consortium for Electronic Business. All rights reserved.
ABSTRACT
Rising cases of corona virus have significantly affected the Indian economy at large. Due to the corona virus outbreak, the Indian economy every day was expected to lose over the US $ 4.5 Billion. (Acuite Ratings). Due to the widespread of covid-19 cases, the Indian Government has lock down the country for quite 60 days which adversely affected commercial activities and the Indian economy. It hinders international trade which in turn stops the import-export of raw materials & hence negatively affected manufacturing at large. Despite the manufacturing sector, various other sectors were also got affected by the corona virus outbreak. The Micro, Small & Medium Enterprises (MSMEs) which are considered to be the backbone of all Indian sectors and also engaged in export activities, has also been impacted by the covid-19 pandemic. MSMEs contributed around 24.63% of GDP from service units as well as 6.11% of the GDP from manufacturing (Confederation of Indian Industry) but this pandemic restricted working and hence made a downfall in the GDP. This paper is based on descriptive analysis based on secondary data. The purpose of the research is to investigate the key areas where the pandemic made its economic influence. It is expected that this study will help design conceptual models for the researcher to overcome this pandemic. Copyright © 2022, Anka Publishers. All rights reserved.
ABSTRACT
This paper aims to identify the revised international marketing strategies in communication during the COVID-19 pandemic by utilizing the firm's resources and capabilities. We conducted in-depth interviews and a questionnaire survey with key stakeholders of retail organizations which changed their digital marketing strategies during COVID-19. The data is collected from 587 respondents from different parts of the world through resource orchestration theory. The qualitative findings support a high degree of association among the firm's resources and capabilities, leveraging processes based on the revised international marketing strategies during the COVID-19 pandemic. We have developed a conceptual model based on these findings with six variables: leveraging process of the firm's capabilities information technology-related resources; information technology-related capabilities, dynamic capabilities, environmental uncertainty, and leveraging process of the firm's resources. However, environmental uncertainty and leveraging of the firm's resources were not influential in forming digital marketing strategies during COVID-19. This study proposes a new process for international marketing managers in business organizations to restructure the resources within their organizations by creating new capabilities and leveraging them.
ABSTRACT
Computational narratives embed data and the computations that process and visualize that data into a story. They introduce some challenges, such as they need to be structured to be easily adapted to a wide range of audiences and contexts, e.g., different technologies providing visual elements for communication. Model-Driven Engineering (MDE) is a paradigm that proposes the specification of models of a specific domain and transformations between them with many purposes. This work aims to analyze computational narratives from the perspective of MDE to address their challenges. We propose a narrative metamodel based on an existing conceptual model, and we explore the definition of model transformations for converting narrative models into HTML and Jupyter documents. We also exemplify the MDE approach using a real-life narrative referring to COVID-19 and provide some ideas for future research lines © 2022 IEEE.
ABSTRACT
Objectives: COVID-19 vaccine boosters are available in many countries. Public health policymakers face difficult choices over which booster brand to recommend, given limited budgets and the need to maximize health gains. Here, we provide a conceptual model to identify the best booster strategies for age-identified subpopulations under different conditions. Method(s): A constrained optimization model with an objective function to minimize bed-days was developed that varied population proportion receiving different booster options by age, to identify the best booster strategy that minimized bed-days with a constraint of maximum healthcare expenditure of US$2.10/person. It included a 3-month decision-tree model to calculate bed-days, with the following health states: healthy/asymptomatic;mild (not hospitalized);moderate (general ward);severe (intensive care unit [ICU], no mechanical ventilation);critical (requiring mechanical ventilation);and death. Medical resource utilization (MRU) costs and hospital bed-days were calculated for each health state. The base country was Brazil. Three booster options, B1 (US$1), B2 (US$2), and no-booster (NB, US>source ) were considered. Based on real-world effectiveness estimates, B1 and B2 were assumed to be 55% and 75% effective against mild/moderate COVID-19, respectively. Both reduced severe/critical COVID-19 by 90%. The target population was adults eligible for boosters, stratified by age. Result(s): The best booster strategy identified recommended 100% coverage of those eligible, with B1 for population <70 years and B2 for population >=70 years. Compared with NB, bed-days were reduced by 75%, hospitalizations by 68%, and ICU admissions by 90% leading to a 60% reduction in total costs (81% reduction in MRU costs). Within individual age-groups, costs were reduced by 57%-66% based on the age-specific disease risk. Conclusion(s): A constrained optimization model identifies the best age-specific booster allocation strategy to minimize hospital bed-days across different age groups without exceeding a predefined budget. Decision-makers could use this method to achieve the best possible health outcomes when healthcare resources are limited. Copyright © 2022