Technology transfer in e-communication for small and medium enterprises as promoters of innovation and competitiveness

Globalization, technological innovations, and the coronavirus disease (COVID-19) pandemic have promoted disruptive changes in buying and selling negotiation models through e-communication. As a result, Small and Medium Enterprises (SMEs) have been forced to adapt to online channels. Considering market relevance, this article describes the survey results with 11 SMEs regarding their adherence to digital media. Moreover, a case study of a selected company demonstrated barriers and propulsions to digital adequacy. The aim was to promote SMEs' competitiveness through technology transfer, focusing on e-communication and strategic digital planning. The results show that the insertion of technology through digital media depends on the knowledge of the tools used in this medium. Therefore, despite being ready to use, SMEs have not yet fully leveraged digital media. Organizational barriers, such as lack of time for those responsible, lack of training and knowledge, and strategic planning, were observed. However, environmental factors such as competitive pressure and innovation-related policies are positive for insertion. Thus, there is room for companies to invest in digital strategic planning focused on improving sales, customer relations, and competitiveness. © 2022 IEEE.

Applications of mathematical modeling and simulation in COVID-19

In this chapter, we describe the use of mathematical and simulation tools applied in various aspects of the coronavirus disease 2019 pandemic through an extensive and careful review of the recently published works. We detailed the existing implementations of models dealing with (i) the spread of the disease, (ii) the prediction of new outbreaks, (iii) the existence of new variants of the virus, (iv) the effects on the at-risk population, (v) the long-term health consequences, (vi) the resource allocation for supportive staffs and clinical beds, (vii) the dynamics of transmission and how to cut the transmission chain, (viii) the impacts of travel restrictions, social distancing and early detection, (ix) the efficacy of prophylactic agents, (x) the effects of optimum interventions, (xi) the impact of existing vaccines, and (xii) the economic effects of the pandemic. © 2023 Elsevier Inc. All rights reserved.

Social CRM as a Business Strategy: Developing the Dynamic Capabilities of Micro and Small Businesses

The global pandemic, caused by the spread of COVID-19, has altered the way people go shopping. In light of this, Social Media channels are an important means of sharing information about goods and services, and different kinds of brands. Since these channels are of considerable market significance, the authors of this paper decided to describe the results of a survey on how to use Social Media to improve customer relationship management processes in 31 companies. The focus was on digital marketing for micro and small businesses. In addition, an in-depth analysis was conducted of four companies, to determine the challenges and strategies in social customer relationship management adopted by micro and small businesses. The results show that this is still a new policy for micro and small companies, but has a great potential to boost sales, enhance customer loyalty and increase brand awareness. The lessons learned can assist policymakers in taking more suitable measures for strengthening this market sector. © 2022, Springer Nature Switzerland AG.

Simulations of Social Distancing Scenarios and Analysis of Strategies to Predict the Spread of COVID-19

The pandemic caused by the novel coronavirus, although more than a year has passed since the first case, still plagues almost the whole world. Several policies have been adopted, especially related to social distancing measures, aiming to mitigate the spread of the disease. Such decisions, in general, take into account simulations capable of providing an overview of the spread of the virus in a given location. Based on the guidelines of the World Health Organization, countries have defined their own policies to fight against the disease, considering economic and social interests. Determining strategies that are increasingly efficient in modeling and simulating such phenomena is essential to support decision making in adverse circumstances. Our objective is to provide a more comprehensive view of strategies for predicting the spread of COVID-19 in the scope of computational modeling and to analyze scenarios capable of describing the impact of social distancing measures. Two different strategies are compared to characterize the virus incubation period, using particular models. Since Italy was one of the countries most affected by the pandemic, despite taking drastic measures to reduce mobility and contact between citizens, we adopt the situation of the early stages of the disease outbreak in this country to demonstrate the numerical results. © 2021, The Author(s), under exclusive license to Springer Nature Switzerland AG.

Explainable Sentiment Analysis Application for Social Media Crisis Management in Retail

Sentiment Analysis techniques enable the automatic extraction of sentiment in social media data, including popular platforms as Twitter. For retailers and marketing analysts, such methods can support the understanding of customers' attitudes towards brands, especially to handle crises that cause behavioural changes in customers, including the COVID-19 pandemic. However, with the increasing adoption of black-box machine learning-based techniques, transparency becomes a need for those stakeholders to understand why a given sentiment is predicted, which is rarely explored for retailers facing social media crises. This study develops an Explainable Sentiment Analysis (XSA) application for Twitter data, and proposes research propositions focused on evaluating such application in a hypothetical crisis management scenario. Particularly, we evaluate, through discussions and a simulated user experiment, the XSA support for understanding customer's needs, as well as if marketing analysts would trust such an application for their decision-making processes. Results illustrate the XSA application can be effective in providing the most important words addressing customers sentiment out of individual tweets, as well as the potential to foster analysts' confidence in such support. Copyright © 2020 by SCITEPRESS-Science and Technology Publications, Lda. All rights reserved.