ABSTRACT
COVID-19 has spread around the world since 2019. Approximately 6.5% of COVID-19 a risk of developing severe disease with high mortality rate. To reduce the mortality rate and provide appropriate treatment, this research established an integrated models with to predict the clinical outcome of COVID-19 patients with clinical, deep learning and radiomics features. To obtain the optimal feature combination for prediction, 9 clinical features combination was selected from all available clinical factors after using LASSO, 18 deep learning features from U-Net architecture, and 9 radiomics features from segmentation result. A total of 213 COVID-19 patients and 335 non-COVID-19 patients from 5 hospitals were enrolled and used as training and test sample in this research. The proposed model obtained an accuracy, precision, recall, specificity, F1-score and ROC curve of 0.971, 0.943, 0.937, 0.974, 0.941 and 0.979, respectively, which exceeds the related work using only clinical, deep learning or radiomics factors. © 2023 SPIE.
ABSTRACT
The COVID-19 pandemic has left scars on the Indian public transportation system. In order to regain its original momentum, policymakers will need to assess the barriers hindering the effectiveness of the public transportation sector. In this regard, this article analyzes the various factors affecting the public transportation sector in India and determines their interrelationships. The research is presented in three steps. First, we review the literature to identify the factors that affect the public transportation system in India. Next, we propose an integrated model of grey-DEMATEL and ANP, grey-DANP, to calculate the priority ranking and weight of the factors. The grey-DEMATEL method is used to find the interrelationships among the factors, while ANP determines the local and global weights of the factors to form a priority order. Then, we present the interrelationships in the form of influential relation maps. Furthermore, we provide a sensitivity analysis to enhance the credibility of our study. The paper reveals that governmental regulations are the most influential factors in India's public transportation system. The transportation authorities and policymakers must also focus on improving the financial stability and enhancing the customer's trust in the public transportation system. The framework provided in this paper can be applied to other countries where similar hindrances in the public transportation system have been caused by COVID-19. © 2023, The Author(s), under exclusive licence to Springer-Verlag GmbH Germany, part of Springer Nature.
ABSTRACT
This paper employed an integrated model for examining behavioral intention to adopt blockchain technology in the supply chain management of manufacturing industries in Bangladesh. The proposed conceptual model was empirically tested using data collected from 189 supply chain managers working in manufacturing organizations in Bangladesh. The findings suggest that perceived usefulness, trading partners' pressure, and competitive pressure are the most important determinant of behavioral intention. © 2023 Taylor & Francis.
ABSTRACT
Purpose: This study relies on an integrated model to study the role of instant mobile messaging apps in the pandemic. The COVID-19 pandemic is reshaping different forms of businesses;one of them is digital marketing. Many aspects of digital marketing augmented in response to the consequences of the virus. A comparative study between Pakistan and Iraq is conducted to investigate the resistors of innovation with the mediation of intention toward actual system usage. It examines the behavioral intentions and actual behavior of individuals in response to the resistance toward innovation. Design/methodology/approach: A total of 800 responses were collected through a convenient sampling method from individuals residing in Pakistan and Iraq in the first wave of COVID-19. The data was analyzed through covariance-based structural equation modeling;SPSS and Smart PLS 3.0 were used as efficient data analysis tools in the study. Findings: The results inferred that individuals are faced with resistance to innovation when they adopt innovative technology. It was inferred that technology adoption is not poised through image both in Pakistan and Iraq. Intention toward actual behavior was determined to be a potential mediator, which enhances the stature of the integrated model. Originality/value: The significance of this study considering practical and theoretical implications is incorporated for marketer's policymakers and consumers, along with recommendations for future research. © 2022, Emerald Publishing Limited.
ABSTRACT
Affected by the COVID-19 epidemic, logistics has received much attention by practitioners and researchers. The paper develops an integrated model for green transportation performance evaluation using the Balanced Scorecard. We propose a set of indicators to evaluate green transportation. These indicators are selected based on Fuzzy-Delphi method following different quantitative judgments of experts. The various criteria are related to the green transportation imperatives especially sustainability, stakeholder engagement and integration, continuous process improvement and green innovation. The proposed Balanced Scorecard is based on progressive methodological steps integrating the precision of the performance levers, the balancing of the components of this performance, the selection of the sustainability factors and the possibility of continuous improvement and adaptation of the selected factors. © 2022, The Author(s), under exclusive license to Springer Nature Switzerland AG.
ABSTRACT
The Vida Decision Support System (Vida) is an application of the Environment-Vulnerability-Decision-Technology (EVDT) integrated modeling framework specifically aimed at COVID-19 impact and response analysis. The development of Vida has been an international collaboration involving multidisciplinary teams of academics, government officials (including public health, economics, environmental, and demographic data collection officials), and others from six states: Angola, Brazil, Chile, Indonesia, Mexico, and the United States. These collaborators have been involved with the identification of decision support needs, the surfacing and creation of relevant data products, and the evaluation of prototypes, with the vision of creating an openly available online platform that integrates earth observation instruments (Landsat, VIIRs, Planet Lab's PlanetScope, NASA's Socioeconomic Data and Applications Center, etc.) with in-situ data sources (COVID-19 case data, local demographic data, policy histories, mobile device-based mobility indices, etc.). Vida both visualizes historical data of relevance to decision-makers and simulates possible future scenarios. The modeling techniques used include system dynamics for public health, EO-based change detection and machine learning for environmental analysis, and discrete-event simulation of policy changes and impacts. In addition to the direct object of this collaboration (the development of Vida), collaborators have also benefited from sharing individual COVID-19-related insights with the network and from considering COVID-19 response in a more integrated fashion. This work outlines the Vida Decision Support System concept and the EVDT framework on which it is based. The international team is using Vida to evaluate the outcomes in several large cities regarding COVID cases, environmental changes, economic changes and policy decisions. It provides an overview of the overlapping and diverging needs and data sources of each of the collaborating teams, as well as how each of those teams have contributed to the development of Vida. The current state of the Vida prototypes and plans for future development will be presented. Additionally, this work will discuss the lessons learned from this development process and their relevance to other integrated applications. Copyright © 2021 by the International Astronautical Federation (IAF). All rights reserved.