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To study the spreading trend and risk of COVID-19, according to the characteristics of COVID-19, this paper proposes a new transmission dynamic model named SLIR(susceptible-low-risk-infected-recovered), based on the classic SIR model by considering government control and personal protection measures. The equilibria, stability and bifurcation of the model are analyzed to reveal the propagation mechanism of COVID-19. In order to improve the prediction accuracy of the model, the least square method is employed to estimate the model parameters based on the real data of COVID-19 in the United States. Finally, the model is used to predict and analyze COVID-19 in the United States. The simulation results show that compared with the traditional SIR model, this model can better predict the spreading trend of COVID-19 in the United States, and the actual official data has further verified its effectiveness. The proposed model can effectively simulate the spreading of COVID-19 and help governments choose appropriate prevention and control measures. Copyright ©2023 Control and Decision.
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Messaging platforms like WhatsApp are some of the largest contributors to the spread of Covid-19 health misinformation but they also play a critical role in disseminating credible information and reaching populations at scale. This study explores the relationships between verification behaviours and intention to share information to users that report high trust in their personal network and users that report high trust in authoritative sources. The study was conducted as a survey delivered through WhatsApp to users of the WHO HealthAlert chatbot service. An adapted theoretical model from news verification behaviours was used to determine the correlation between the constructs. Due to an excellent response, 5477 usable responses were obtained, so the adapted research model could be tested by means of a Structural Equation Model (SEM) using the partial least squares algorithm on SmartPLS4. The findings suggest significant correlations between the constructs and suggest that participants that have reported high levels of trust in authoritative sources are less likely to share information due to their increased behaviours to verify information. © 2023 IEEE.
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According to World Bank statistics in 2019, Indonesia ranked two in the average unemployment rate with 5.28% in South East Asia. Although the unemployment rate can be reduced by an equitable distribution of human resource empowerment and national development, the global pandemic COVID-19 made a major impact on increasing the rate of unemployment. This paper tests the spatial autocorrelation on the average unemployment in Indonesia using Ordinary Least Squares (OLS) and Moran's I. The OLS method was used to examine the effects that affect the unemployment rate using an independent variable. In contrast, the Moran's I used to prove the existence of spatial effect on the level of movement in Indonesia. From the experiment, there are four variables that influence the unemployment rate by using the OLS modeling method. The Moran's I test showed a p-value = 0.006 with α = 0.05. Therefore, there is a spatial autocorrelation between provinces in Indonesia. In addition, the model is tested using the Variance Inflation Factor. The model showed a VIF score ¡10, therefore there is no collinearity and the assumption is fulfilled. The model is also being tested using dwtest, bptest, and Lilliefors test. The result showed p-value = 0.6231 for dwtest, p-value = 0.932 for bptest, and p-value = 0.08438 for Lilliefors test.. © 2022 IEEE.
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SARS-CoV-2 is an infection that affects several organs and has a wide range of symptoms in addition to producing severe acute respiratory syndrome. Millions of individuals were infected when it first started because of how quickly it travelled from its starting location to nearby countries. Anticipating positive Covid-19 incidences is required in order to better understand future risk and take the proper preventative and precautionary measures. As a result, it is critical to create mathematical models that are durable and have as few prediction errors as possible. This study suggests a unique hybrid strategy for examining the status of Covid-19 confirmed patients in conjunction with complete vaccination. First, the selective opposition technique is initially included into the Grey Wolf Optimizer (GWO) in this study to improve the exploration and exploitation capacity for the given challenge. Second, to execute the prediction task with the optimized hyper-parameter values, the Least Squares Support Vector Machines (LSSVM) method is integrated with Selective Opposition based GWO as an objective function. The data source includes daily occurrences of confirmed cases in Malaysia from February 24, 2021 to July 27, 2022. Based on the experimental results, this paper shows that SOGWO-LSSVM outperforms a few other hybrid techniques with ideally adjusted parameters. © 2022 IEEE.
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The COVID-19 pandemic has resulted in a rapid growth of online learning. While majority of the current research focus on different learning management systems, massive open online courses, or even specific softwares like Zoom and Microsoft Teams, the use of artificial-intelligence (AI) based voice assistants (VAs) for the purpose of online education is very rare. In this work we propose, validate, and test a research model that explains the continuance usage of VAs by students for learning purpose during their home quarantine period. We consider novel pandemic-specific psychological factors like loneliness and self-quarantine, together with anthropomorphic factors like voice attractiveness of the VAs for proposing the research model. The factors of satisfaction and continuance usage are borrowed from Expectation Confirmation Theory. Partial Least Squares Structural Equation Modelling is used for testing the proposed model. © 2023 IEEE.
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The COVID-19 pandemic has spread all over the world. People go to public or crowded areas (i.e., schools, universities, hospitals, and government agencies), they take a lot of time to be checked the fever symptoms because of coronavirus. Therefore, this paper presents a method to automatically detect the body temperature by distance based on the recursive least square estimation. An infrared thermal camera is utilized to measure both human and environmental temperatures in real-time within a two-meter distance. The recursive least square approach is applied to estimate parameters for these correct temperatures. A microcontroller is integrated to read, compute, and send the measured temperatures to both web browsers and smartphones using the message queuing telemetry protocol. Moreover, the module of radio frequency identification is utilized for identification of the personal information. To validate our proposed temperature measurement system, fifteen male healthy students are invited to record their body temperature. The experimental result showed that our proposed approach was the correct temperature compared with the commercial device (37 ± 0.17 ° C). However, our proposed system is more stable than the commercial device: the standard deviation of the commercial device and ours is 0.41 C and 0.09°C, respectively. The measured temperature of each person is monitored and stored in the cloud. It is easily accessed by web browsers and smartphones. In addition, our proposed system can show a warning if the measured temperature is greater than the threshold. This work promises to automatically initial selection for suspected cases of COVID-19 disease to reduce the infection of this pandemic. © 2022 IEEE.
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This research explores the opportunities presented by COVID-19 for green supply chains' environmental practices and ecological sustainability performances in the healthcare sector. This study investigates the connections between uncertainty-fear of COVID-19, healthcare green supply chain management (GSCM), and the three pillars of a firm's sustainability performance (environmental, economic, and social). Moreover, this study examines the moderating role of social media usage (SMU) on the effect of uncertainty-fear of COVID-19 on healthcare-GSCM. When conducting the empirical part, this study uses the partial least squares structural equation modeling method based on a sample of 483 healthcare managers. The findings prove that the uncertainty-fear of COVID-19 has a beneficial impact on healthcare-GSCM. Besides, SMU moderates the relationship between uncertainty-fear of COVID-19 and healthcare-GSCM, indicating the importance of SMU in gathering information for the healthcare sector during COVID-19. Likewise, when interacting with healthcare firms' sustainability performances, healthcare-GSCM positively impacts environmental and social performances, though it has a negligible impact on economic performance. This study adds to the “social cognitive theory”by introducing the concept of uncertainty-fear of COVID-19. Furthermore, this research adds to the “resource-based view theory”and the “knowledge-based view theory”by exploring the SMU's role during the outbreak. IEEE
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The pandemic of Covid-19 requires people in any profession to do large-scale social restrictions, this also lead in financial/external auditors experiencing difficulties in conducting audits in the common daily activity, which is by visiting clients physically to make observations. In this condition, online observation using remote audit become one of the solution. The purpose of this study is to analyze the effectiveness and efficiency of external auditors in transition to remote auditing due to the Covid-19 Pandemic. The data collection technique is using primary data from questionnaire. We distribute questionnaire to Public Accounting Firms located in DKI Jakarta using simple random sampling method technique. The method for data analysis is using partial least squares conducted with Software of SmartPLS 3. The result of this study indicates that remote audit efficiency and remote audit efficiency have positive and significant effect on audit quality. Meanwhile, institutional support has no significant effect on audit quality. © 2022 IEEE.
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The era of industrial revolution 4.0 has introduced new technology that makes all of the activities in this world change. At the same time, the Covid-19 pandemic outbreak has made social distancing which make auditors must adopt technology digital to be able perform remote audit. Based on that explanation, we conducted research on the effect of remote audit, work experience, work overload, transformational leadership, and emotional intelligence on auditor performance. Our research used quantitative method, we use primary data from questionnaires that were distributed to auditors who work in Public Accounting Firms in Jabodetabek. The data analysis method used was Structural Equation Model (SEM) based on Partial Least Square (PLS) with SmartPLS 3.2.9 software. Our results showed that work experience, transformational leadership, and emotional intelligence have a significant effect on auditor work performance, while remote audit and work overload have no significant effect on auditor performance. © 2022 ACM.
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The purpose of this study was to test the relationship of influence of ease of use and perceived usefulness on motivation, collaboration, and behavioral intention in university students in times of Covid-19. The methodology used for the study corresponds to a non-experimental investigation, a questionnaire was applied to a convenience sample of 530 university students (n=19;α=0.944 ω=0.946), using Factor Exploratory and Confirmatory Analysis as tests of validity and reliability, through the Modeling of Structural Equations of Partial Least Squares PLS-SEM. The results have shown that there is a positive effect of causality of perceived ease of use on student collaboration, student motivation and perceived usefulness;in the same way, there exists a causal relationship between the perceived usefulness and the student's collaboration, the intention of the behavior and the student's motivation. Contrarily, there would not be an influence relationship between perceived ease of use on behavioral intention in university students in a context of Covid-19. © 2022 IEEE.
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The subscription of digital services has increased due to the COVID-19 pandemic. However, this was not the same for digital news subscription which remained low. Therefore, this study looks to study the factors that influence the resistance to digital news subscription during the COVID-19 pandemic. In order to achieve this, the Innovation Resistance Theory was applied. Data was collected through an online survey that yielded 199 responses. Based on the results of the data analysis, two out of the five barriers were revealed to have insignificant relationships with resistance. With that said, value barrier, risk barrier, and image barrier were established as significant facilitators of resistance. Several insights were then proposed to news media companies. Moreover, this study fills the theoretical gap of comprehending the antecedents of resistance on digital news during the COVID-19 pandemic. © 2023, The Author(s), under exclusive license to Springer Nature Switzerland AG.
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Various countries have developed contact tracing applications to prevent the spread of COVID-19 outbreaks. For example, Indonesia launched a government surveillance technology named PeduliLindungi as a contact tracing application for COVID-19. This empirical paper aims to assess the explanatory power of the Expectation-Confirmation Model (ECM) by adding three new constructs, perceived security, perceived privacy, and effort expectancy, concerning the users' continuance usage of contact tracing applications. A survey instrument was developed for PeduliLindungi application users, with survey participants (N=535) recruited from Indonesia. The study tested the model using partial least squares structural equation modeling. The results showed that effort expectancy is the most significant factor in continuance intention mediated by satisfaction. Meanwhile, perceived privacy does not affect continuance intention mediated by satisfaction. © 2022 IEEE.
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Purpose: The Coronavirus disease 2019 (COVID-19) pandemic has increased the use of food delivery containers in the food and beverage industry. Based on the theory of planned behavior (TPB), the aim of this paper is twofold: Firstly, it examines the influence of three elements of TPB (attitude, perceived behavioral control and subjective norm) and time pressure on the intention to reuse reusable food delivery containers (ITR). Secondly, it examines ITR as an antecedent to the willingness to pay more for reusable food delivery containers (WTPM). Design/methodology/approach: Data were collected from 401 higher education institution (HEI) students and analyzed using partial least squares structural equation modelling (PLS-SEM). Findings: The study found that the three elements of TPB influenced ITR. Furthermore, the results revealed that ITR directly influenced WTPM. Surprisingly, time pressure did not influence ITR. Originality/value: The research is one of the earliest studies to investigate HEI students' intention to reuse food delivery containers during the COVID-19 pandemic. The study contributes to TPB by presenting a novel, integrated model to explain the independent roles of time pressure and ITR on ITR and WTPM, respectively. Finally, it contributes to the existing body of knowledge on pro-environmental behavior among HEI students and advances methodologically by establishing the PLS-SEM approach. © 2023, Emerald Publishing Limited.
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Purpose: Coronavirus disease 2019-related fake news consistently appears on social media. This study uses appraisal theory to analyze the impact of such rumors on individuals' emotions, motivations, and intentions to share fake news. Furthermore, the concept of psychological distance and construal level theory are used in combination with appraisal theory to compare toilet paper shortages and celebrity scandal rumors. Design/methodology/approach: Data collected from 299 Taiwanese respondents to 150 toilet paper shortage-related and 149 celebrity gossip-related questionnaires were processed using partial least squares regression and multigroup analysis. Findings: In both cases, surprise is felt most intensely. However, unlike in the celebrity fake news scenario, worry plays a prominent role in driving the altruistic sharing motivation related to the toilet paper shortage rumor. Furthermore, while emotional attributes (basic or self-conscious, concrete, or ) serve as a guide for how emotions change with psychological distance, the degree to which an emotion is relevant to the fake news context is key to its manifestation. Originality/value: This study examines the impact of individuals' emotions on their motivations and intention to share fake news, applying the appraisal theory and the psychological distance concept in a single study to fake news sharing intention. It evaluates the relationship between psychological distance and emotions, revealing that it is not absolute and need not necessarily shift according to psychological distance change;rather, the relationship is context-sensitive. © 2022, Emerald Publishing Limited.
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Purpose: Even though social media (SM) has been explored in-depth, its role remains unclear regarding short- and long-term preventive attitudes in global health emergencies. To fill this gap, the Stimulus-Organism-Response framework aims to clarify the social media exposure mission in acknowledging risk perception and triggering preventive attitudes and behaviors toward COVID-19 and general vaccination. Design/methodology/approach: The authors conducted an explanatory-predictive study on 480 Romanian students, using partial least squares structural equation modeling, and performed model evaluation, multi-group, model selection, and importance-performance map analyses. Findings: The study provides insights in understanding significant relationships and drivers explaining and predicting attitudes towards vaccines. The main relationships are between fear and risk perception;risk and preventive attitudes and behaviors;and vaccination degree and attitudes to vaccines. The most important factor is the vaccination degree and media exposure is the most performant. Practical implications: Developing and applying regulations and communication strategies for quality mass information may positively increase attitudes toward vaccines by indirectly enforcing the main drivers. Social implications: Organizations, authorities, and opinion leaders must have a coherent supportive presence in media. Originality/value: This study filled the literature gap by building a generic theoretical and empirical proven framework that investigates the mediated effect towards vaccines of all media types by COVID-19 experience and vaccination degree. Peer review: The peer review history for this article is available at: https://publons.com/publon/10.1108/OIR-11-2021-0621. © 2022, Emerald Publishing Limited.
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Purpose: This study aims to investigate technology-based health and safety (H&S) management to control the spread of disease on construction sites using a partial least squares structural equation modelling (PLS-SEM) approach. Design/methodology/approach: An extensive literature review is conducted to develop a conceptual framework. The variables identified from the literature review are included in a cross-sectional survey which gathered a total of 203 valid feedback. The variables for challenges are grouped under their relevant construct using exploratory factor analysis. Then, a hypothesized model is developed for PLS-SEM analysis using Smart PLS software. Later, the outcome of the model is further validated by nine construction experts using a semi-structured questionnaire survey. Findings: The results rationalized the relationships between the COVID-19 H&S measures, challenges in implementing COVID-19 H&S measures on construction sites and the innovative technologies in transforming construction H&S management during the COVID-19 pandemic. The possible challenges that obstruct the implementation of H&S measures are highlighted. The potential technologies which can significantly transform H&S management by reducing the impact of challenges are presented. Practical implications: The findings benefited the industry practitioners who are suffering disruption in construction operations due to the pneumonic plague. Originality/value: By developing a conceptual model, this study reveals the contribution of technology-based H&S management for construction projects during the COVID-19 pandemic, which remains under-studied, especially in the context of the developing world. © 2022, Emerald Publishing Limited.
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Purpose: The purpose of this study was to demonstrate a cloud business intelligence model for industrial SMEs. An initial model was developed to accomplish this, followed by validation and finalization of the cloud business intelligence model. Additionally, this research employs a mixed-techniques approach, including both qualitative and quantitative methods. This paper aims to achieve the following objectives: (1) Recognize the Cloud business intelligence concepts. (2) Identify the role of cloud BI in SMEs. (3) Identify the factors that affect the design and presenting a Cloud business intelligence model based on critical factors affecting SMEs during pandemic COVID-19. (4) Discuss the importance of Cloud BI in pandemic COVID-19 for SMEs. (5) Provide managerial implications for using Cloud BI effectively in Iran's SMEs. Design/methodology/approach: In the current study, an initial model was first proposed, and the cloud business intelligence model was then validated and finalized. Moreover, this study uses a mixed-methods design in which both qualitative and quantitative methods are used. The fuzzy Delphi Method has been applied for parameter validation purposes, and eventually, the Cloud business intelligence model has been presented through exploiting the interpretive structural modeling. The partial least squares method was also applied to validate the model. Data were also analyzed using the MAXQDA and Smart PLS software package. Findings: In this research, from the elimination of synonym and frequently repeated factors and classification of final factors, six main factors, 24 subfactors and 24 identifiers were discovered from the texts of the relevant papers and interviews conducted with 19 experts in the area of BI and Cloud computing. The main factors of our research include drivers, enablers, competencies, critical success factors, SME characteristics and adoption. The subfactors of included competitors pressure, decision-making time, data access, data analysis and calculations, budget, clear view, clear missions, BI tools, data infrastructure, information merging, business key sector, data owner, business process, data resource, data quality, IT skill, organizational preparedness, innovation orientation, SME characteristics, SME activity, SME structure, BI maturity, standardization, agility, balances between BI systems and business strategies. Then, the quantitative part continued with the fuzzy Delphi technique in which two factors, decision-making time and agility, were deleted in the first round, and the second round was conducted for the rest of the factors. In that step, 24 factors were assessed based on the opinions of 19 experts. In the second round, none of the factors were removed, and thus the Delphi analysis was concluded. Next, data analysis was carried out by building the structural self-interaction matrix to present the model. According to the results, adoptability is a first-level or dependent variable. Regarding the results of interpretive structural modeling (ISM), the variable of critical success factors is a second-level variable. Enablers, competencies and SME characteristics are the third-level and most effective variables of the model. Accordingly, the initial model of Cloud BI for SMEs is presented as follows: The results of ISM revealed the impact of SME characteristics on BI critical success factors and adoptability. Since this category was not an underlying category of BI;thus, it played the role of a moderating variable for the impact of critical success factors on adoptability in the final model. Research limitations/implications: Since this study is limited to about 100 SMEs in the north of Iran, results should be applied cautiously to SMEs in other countries. Generalizing the study's results to other industries and geographic regions should be done with care since management perceptions, and financial condition of a business vary significantly. Additionally, the topic of business intelligence in SMEs constrained the sample from the start since not all SMEs use business int lligence systems, and others are unaware of their advantages. BI tools enable the effective management of companies of all sizes by providing analytic data and critical performance indicators. In general, SMEs used fewer business intelligence technologies than big companies. According to studies, SMEs understand the value of simplifying their information resources to make critical business choices. Additionally, they are aware of the market's abundance of business intelligence products. However, many SMEs lack the technical knowledge necessary to choose the optimal tool combination. In light of the frequently significant investment required to implement BI approaches, a viable alternative for SMEs may be to adopt cloud computing solutions that enable organizations to strengthen their systems and information technologies on a pay-per-use basis while also providing access to cutting-edge BI technologies at a reasonable price. Practical implications: Before the implementation of Cloud BI in SMEs, condition of driver, competency and critical success factor of SMEs should also be considered. These will help to define the significant resources and skills that form the strategic edge and lead to the success of Cloud BI projects. Originality/value: Most of the previous studies have been focused on factors such as critical success factors in cloud business intelligence and cloud computing in small and medium-sized enterprises, cloud business intelligence adoption models, the services used in cloud business intelligence, the factors involved in acceptance of cloud business intelligence, the challenges and advantages of cloud business intelligence, and drivers and barriers to cloud business intelligence. None of the studied resources proposed any comprehensive model for designing and implementing cloud business intelligence in small and medium-sized enterprises;they only investigated some of the aspects of this issue. © 2021, Emerald Publishing Limited.
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The COVID-19 pandemic boosted the digital transformation of many services, including healthcare, and access to medical care using teleconsultation has increased rapidly. Thus, a growing number of online platforms have been developed to accommodate patients' needs. This paper examines the factors that predict the intention to use medical teleconsultation by extending the unified theory of acceptance and use of technology (UTAUT2) with the three dimensions of trusting beliefs and self-efficacy. A survey was administered to patients who had used a teleconsultation platform during the pandemic period. As one of the largest studies to date, a sample of 1233 respondents was collected and analyzed using a partial least squares approach, often mobilized in the information systems (IS) domain. Furthermore, a deep analysis using all recommended metrics was performed. The results highlight the significance of trusting beliefs, and self-efficacy in the adoption of digital healthcare services. These findings contribute to both theory and practice in COVID-19 research. © 2022 Elsevier Ltd
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This paper examines the role of Intellectual Capital (IC) and its contribution to Business Sustainability (BS) among Large Manufacturing Firms (LMF) in Malaysia. It seeks to explain the relationship between them under turbulent market conditions. The study used the survey method to collect data from 203 large companies, and the hypotheses were tested using Partial-Least Squares-Structural Equation Modeling. Based on the findings, two dimensions of IC, namely Human capital (HC) and Structural Capital (SC), had a significant effect on business sustainability, but Relational Capital (RC) did not. Also results indicate that Market Turbulence (MT) moderates the relationship between two IC dimensions, HC and RC but not that between SC and BS. The study findings can be used as guidelines by CEOs of LMFs, policy makers and researchers to comprehend positive the influence of MT and IC on BS. © 2022
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An epidemic Susceptible-Infected-Removal (SIR) model with vital dynamics of birth and death rates is presented on a network by using graph Laplacian diffusion. Migration parameter has been introduced for controlling the population mobility between different regions. The subsequent waves for the infected occur under some restrictions on the migration parameter. Isolation strategies are investigated for different types of networks. Finally, we estimate important model parameters using the Least-Square method. © 2022 IEEE.