Diego G. Chevarria

Bio: Diego G. Chevarria is an academic researcher from Federal Institute of Rio Grande do Sul. The author has contributed to research in topics: Donation. The author has an hindex of 1, co-authored 1 publications receiving 1 citations.

Considerations Regarding Donation and Value Co-Creation in Times of COVID-19 Pandemic

Abstract: This paper examines the phenomenon of strategic donation (including fundraising and intention to donate) through the lens of value co-creation before and after the outbreak of the COVID-19 in non-profit organizations (NPOs). The methodology was based on interviews and statistical analyses of online data. The qualitative results demonstrated that within NPOs, neither the marketing strategy nor the fundraising has been greatly affected by the COVID-19 pandemic. NPOs employ a variety of strategies, including value co-creation activities (events), which is a key element in influencing engagement and donation. The quantitative findings showed that “dialogue” is the most frequent of the value co-creation elements (dialogue, access, risk sharing, and transparency—DART) in the media (posts) under consideration. In general, linear regression indicated that, after the beginning of the pandemic, these DART elements may predict online interaction and intention to donate. Shares and comments had a weak R2 before the pandemic outbreak and a strong R2 after it; that may be explained by the fact that people spent more time online after the outbreak.

Economic Efficiency of Outsourcing Business Models: A Comparative Assessment

Abstract: This study aims to form a methodological approach to assess outsourcing business models and identify the most acceptable one for a modern enterprise. The research methodology is based on the author's approach, which includes cognitive map analysis and a simplicial complex. The study was tested on two Information Technology companies in Russia. Based on the determination of the profit elasticity on the manageable vertices of outsourcing business models, the most attractive in terms of efficiency criterion in the form of profit is the outsourcing business model of developing in-house non-IT services. The analysis of structural connectivity made it possible to rank the factors by the level of importance for the preservation of the business model. Modeling the effectiveness of implementing the formed outsourcing business models provided an opportunity to increase profits for the investigated IT companies by increasing the number of single-type projects. The conducted modeling of changes in relations with customers in the studied IT enterprises shows the inexpediency of changing customer relations in BM3. It is proved that certain factors can be replaced without losing the integrity of the business model. The scientific contribution of this study is the proposed methodological approach for assessing the effectiveness of an outsourcing business model. Based on the application of this methodology, the strategic objectives are linked to the business model in the process of achieving them (the achievement of strategic objectives under the influence of the selected outsourcing business model is shown).

Modeling a COVID-19 Vaccination Campaign in the State of Madhya Pradesh, India

Abstract: COVID-19 vaccination campaigns have been launched across the globe to mitigate the impact of the COVID-19 disease. However, COVID-19 vaccination campaigns (Vaccination campaigns are the complete process of COVID-19 vaccination campaigns beyond just administrating vaccines.) are a complex multi-stakeholder process, and therefore, it is important to understand the key components and drivers of vaccination campaigns to help devise strategies to increase vaccination coverage for existing and future vaccination efforts. A system dynamics modeling approach was used to trace the vaccination campaign for the Indian state of Madhya Pradesh. The results identified the key stakeholders of the vaccination campaign and their inter-linkages, and the diverse perspectives of stakeholders of vaccination campaigns in Madhya Pradesh were collated in a structured format. Further, system dynamics models were developed to capture all aspects of the vaccination campaign in Madhya Pradesh, including the challenges and innovations. The outcomes of the study can assist academicians, practitioners, and policymakers develop vaccination programs at sub-national, national, and global levels. They will guide decision-makers to take preemptive measures to mitigate possible risks and challenges and provide improved services as part of vaccination campaigns.The online version contains supplementary material available at 10.1007/s40171-022-00326-9.

Crisis Management and Planning in Portuguese Nonprofit Organizations During the COVID-19 Pandemic

Abstract: The COVID-19 pandemic has created several challenges for all organizations. However, Nonprofit Organizations (NPOs), due to their unique specificities, when compared to other types of organizations, face unique challenges. NPOs are extremely vulnerable during crisis, although the literature suggests that it is not known to what extent these organizations are prepared to deal with crises and have proper crisis management and planning strategies. Given this literature gap, this research aims to better understand the impact of this crisis on Portuguese NPOs through the research question: What is the impact of a crisis like COVID-19 on NPOs’ perceptions of crisis management and planning? A mixed method is used, including document analysis, qualitative interviews, and a quantitative methodology through a questionnaire survey. Study 1 provides an explanation on why Portuguese NPOs had no planning and were unprepared to cope with the COVID-19 pandemic. Study 2, comprising a larger sample, diagnoses and suggests an insufficient level of planning and preparedness as the main finding, substantiated by the lack of planning activities, teams, infrastructures, and communication practices. The findings of each study, implications, and avenues for future research are addressed.

Prescriptive Analytics-Based SIRM Model for Predicting Covid-19 Outbreak

Abstract: Predicting the outbreak of a pandemic is an important measure in order to help saving people lives threatened by Covid-19. Having information about the possible spread of the pandemic, authorities and people can make better decisions. For example, such analyses help developing better strategies for distributing vaccines and medicines. This paper has modified the original Susceptible-Infectious-Recovered (SIR) model to Susceptible-Immune-Infected-Recovered (SIRM) which includes the Immunity ratio as a parameter to enhance the prediction of the pandemic. SIR is a widely used model to predict the spread of a pandemic. Many types of pandemics imply many variants of the SIR models which make it very difficult to find out the best model that matches the running pandemic. The simulation of this paper used the published data about the spread of the pandemic in order to examine our new SIRM. The results showed clearly that our new SIRM covering the aspects of vaccine and medicine is an appropriate model to predict the behavior of the pandemic.