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This study aims to determine how the most sustainable brands in Italy and Spain developed communication and awareness-raising actions during the COVID-19 pandemic and whether these companies were truly involved in raising public awareness of the pandemic. The authors specifically focus on sustainable companies, as health communication is considered to be an important corporate social responsibility task.

To answer these questions, the authors have used data on the social media activity (Twitter and Instagram) of these brands in Spain and Italy, extracting the posts and associated hashtags that each of them has published throughout the pandemic to be processed using social network analysis and visualization techniques.

The detailed analysis of both the levels of activity and the content of the messages provides interesting insights into the communication models of the companies and the influence of factors such as time, country and the specific social media platform used.

The authors analyze the communication of the most sustainable businesses on social media during the pandemic, adopting a highly innovative approach. The particular originality of this study lies in the parallel analysis of two different countries that were simultaneously shaken by the pandemic in very similar circumstances. This study also presents a novel use of graphical representation tools in terms of companies’ behavior for health communication on social media.

El objetivo de esta investigación es determinar cómo las marcas reconocidas como las más sostenibles en Italia y España han desarrollado acciones de comunicación durante la pandemia del Covid-19 y si estas empresas se han involucrado realmente en la sensibilización pública de la pandemia. Nos centramos específicamente en las empresas sostenibles dado que la Comunicación en Salud se considera una tarea importante de responsabilidad social corporativa.

Para responder a estas preguntas, hemos utilizado datos de actividad en medios sociales (Twitter e Instagram) de estas marcas en España e Italia, extrayendo los posts y hashtags asociados que cada una ha publicado a lo largo de la pandemia para procesarlos usando técnicas de análisis y visualización de redes sociales.

El análisis detallado tanto de los niveles de actividad como del contenido de los mensajes permite obtener conclusiones interesantes sobre los modelos de comunicación de las empresas y la influencia de factores como el tiempo, el país y el medio social concreto utilizado.

Analizamos la comunicación realizada por las compañías más sostenibles en medios sociales durante la pandemia, adoptando un enfoque muy innovador. La particularidad de este estudio radica en el análisis paralelo de dos países diferentes que fueron sacudidos simultáneamente por la pandemia en circunstancias muy similares. Este estudio también conlleva un uso novedoso de herramientas de representación gráfica en términos del comportamiento de las empresas para Comunicación en Salud en medios sociales.

本研究的目的是确定在意大利和西班牙被认为是最可持续发展的品牌在Covid-19大流行期间是如何开展传播行动的, 以及这些公司是否真正参与了提高公众对该大流行病的认识。我们特别关注可持续发展的公司, 因为健康传播被认为是企业社会责任的一项重要任务。

为了回答这些问题, 我们使用了这些品牌在西班牙和意大利的社交媒体活动数据（Twitter和Instagram）, 提取了每个品牌在整个大流行期间发布的帖子和相关标签, 并使用社交网络分析和可视化技术进行处理。

通过对活动水平和信息内容的详细分析, 可以得出关于这些公司的传播模式以及诸如时间、国家和所使用的特定社交媒体等因素的影响的有趣结论。

我们分析了最可持续的公司在大流行期间在社交媒体上进行的传播, 采取了一种非常创新的方法。这项研究的特殊性在于对两个不同国家的平行分析, 这两个国家在非常相似的情况下同时受到大流行病的冲击。这项研究还包括在社交媒体上对公司健康传播行为的图形表示工具的新颖使用。

The power systems behavior is nonlinear, and this is reflected in that the measurement signals are composed by multi-components. Thus, this paper aims to present a method for analyzing multi-component signals that allow calculating signal parameters such as frequency, damping constant, amplitude and phase for each component, as well as determining the direct current component.

The method proposed is based in the Z-transform of a damped sinusoidal signal with direct current. Only the Z-transform poles are used to form equation systems which are used to obtain frequency and damping. Then, the amplitude, the phase and the direct current component are determined by the above results.

The method is able to determine frequencies, damping constants, phases and amplitudes of the different modal components of a signal using only a few measurements. Moreover, the method does not require filter banks tuned with some previous knowledge of signal’s characteristics. The presented test cases of field measured signals show the good performance of the proposed method, which is able to obtain the parameters of interest with a very short observation window.

One quality of this method is that it has a very short delay to reach the first solution and from there you get one result each sample; the delay time is equivalent to 2 + 4C samples where C is the number of components in the signal. Finally, it is concluded that because of the small number of samples that are needed and the low algorithmic complexity of the methodology, the method is apt to make applications in real time.

Most systems have a non-linear (NL) behavior and measured signals reflect this non-linearity such that in general they are composed with more than one sinusoidal component. NL analysis methods represent an option for analyzing such signals, however these methods have been developed for single frequency signals, this forces to implement a components separation procedure before performing the signal analysis. The purpose of this paper is to present a new method for analyzing multi-component signals that allows calculating amplitude, frequency and damping constants of the contained sinusoidal components. The method is able to simultaneously identify the different components within a detection bandwidth without previous separation of mono-components, as needed for most methods in used today.

The method proposed in this work characterizes sinusoidal signals determining their amplitude, frequency and damping constant. This method is based on transforming from the time domain to the z-domain an oscillatory signal that may or may not possess damping. Since frequency and damping of a signal can be determined knowing its z-domain poles, using the signal in z-transform domain an equations system to find the signal poles can be written.

From the results it can be concluded that the proposed method is reliable and consistent. One quality of the method is its short delay, when the procedure starts there is a delay equal to the time needed to accumulate four samples for each detectable frequency in order to perform the first calculation, after this, the algorithm can deliver a result at each sampling instant. This short delay and the low complexity of the algorithm can permit using the method in real time applications.

The proposed method is able to determine frequencies, damping constants and amplitudes of the components of a signal without a previous separation of mono-components, in contrast with other methods that require filter banks tuned using a previous knowledge of the signal. Moreover unlike techniques such as the Hilbert-Huang Transform the proposed method can be applied to signals with components having very close frequencies.

Meetings, incentives, conventions/conferences and exhibitions (MICE) tourism is a segment of business travel, which is experiencing a process of disintermediation. Using the value chain concept, this study aims to analyze the role and value of intermediaries in the MICE value chain. As the interests and perceptions of stakeholders are different, the authors also study if there is consensus or dissonance in their opinion.

This study uses mixed methods. First, by means of interviews with MICE professionals to identify the research variables and validate the test sample and questionnaire. Then, an international survey, which uses logistic regressions to identify the variables that support value. The post-hoc ANOVA test identifies the differences of opinions and determines the existence of consensus or dissonance.

Incoming agents create value by means of convenience and good rates and outbound agents by trust. The incoming agent is more valued and enjoys a position of power and therefore has more chances of remaining active in the market. However, there is no consensus about the role of intermediaries, hotels being the most dissonant stakeholder.

Instead of focusing on the negative aspects of disintermediation, this study uses a multifaceted perspective to identify the reasons that lead to value creation by intermediaries. This is vital for MICE stakeholders to acknowledge disintermediation and act consequently. Conclusions can also provide valuable guidance for intermediaries in other business to business interactions to better understand their value, competitive advantages and position of power.

This study aims to understand how the institutional and populational characteristics of a Brazilian city, that is, size, gross domestic product (GDP), life expectancy, education, violence and amount of workers benefiting from PAT (Workers’ Food Program) bias the agglomeration of fast-food companies.

The research involved 7,653 units distributed among 270 brands of fast-food chains (9 foreign and 261 Brazilian) operating in 542 Brazilian cities in 2015 and institutional and populational characteristics information about them. It calculated the Herfindahl index and implemented mixed inflated beta models.

The study found out that the agglomeration of establishments is mainly associated with the city’s income per capita, education, GDP and with some differences regarding the origin of the company, Brazilian or foreign.

The limitations of the study are the availability of Brazilian cities' data and information about the fast-food companies, such as governance-related information and general infrastructure. The study was cross-sectional, which does not analyze the business installation speed.

This work provides data collection and analyzes which factors may contribute to the knowledge of the Brazilian fast-food market. It stands out that foreign companies do not seem to contemplate city violence. The proposed models can serve as an investors’ foundation to start, expand business and predict the number of establishments in a city.

The study highlights the relation between the cities’ institutional and populational characteristics and the aggregation of fast-food chains in Brazilian cities, using index commonly applied in industrial agglomeration.

The purpose of this paper is to introduce a model for the knowledge‐based development (KBD) of a region using a research chair strategy at Tecnológico de Monterrey, to describe its impact and to propose its use in organizations that generate scientific and technological knowledge, especially research groups, in a university environment.

The approach employed in this research evolves around a strategy for setting up research chairs (research groups headed by a lead investigator) which is a type of action research methodology whose steps are: planning a research program which is clear, focused and with an impact on regional development, implementing it, observing the corresponding processes and results, and reflecting on them. The components of the KBD model include human and intellectual capital (research professors and research students), research products (journal articles, conference papers, books and patents), research funding, entrepreneurial spin‐offs emerging from the research capacities, and research‐based learning and education. Measures of performance for each of these components are explained and quantified for the KBD at Tecnológico de Monterrey. Management and technological issues are analyzed in deploying and implementing the research chair strategy, especially the method proposed for evaluating research chairs. An overall assessment of the approach is given based on the results of five years of operation. The internal and external impact of the model and its computer implementation are also analyzed and assessed.

This paper concludes that research outcomes at universities, research centers and institutes may be organized around a knowledge‐based model and a knowledge‐information computer system that supports the model. These serve the organization by disseminating knowledge assets, by solving economic and social needs in different regions, and by creating value for researchers and for the organization.

The paper describes a knowledge‐based model that proved useful for a university case. It can be adapted by organizations that generate knowledge and need to leverage it, not only for their own benefit but also as an engine of economic development for target regions. The model is supported by a knowledge‐information computer system and has been running for five years.

Strategic planning (SP) enables enterprises to plan management and operations activities efficiently in the medium and large term. During its implementation, many processes and methods are manually applied and may be time consuming. The purpose of this paper is to introduce an automatic method to define strategic plans by using text mining (TM) algorithms within a generic SP model especially suited for small- and medium-sized enterprises (SMEs).

Textual feedbacks were collected through a SWOT matrix during the implementation of a SP model in a company dedicated to the local distribution of food. A four-step TM process (performing acquisition, pre-processing, processing, and validation tasks) is applied via a framework developed under the cloud computer paradigm in order to determine the strategic plans.

The use of categorization and clustering algorithms show that unstructured textual information produced during the SP can be efficiently processed and capitalized. Collected evidence reveals the potential to enhance the strategic plans creation with less effort and time, improving the relevance, and producing new technological resources accessible to SMEs.

An innovative framework especially suited for the SMEs based on the synergy assumption of the coupling between TM and a generic SP model.

We present a critical literature review debating Brazilian research on social and environmental accounting (SEA). The aim of this study is to understand the role of politics in the construction of hegemonies in SEA research in Brazil. In particular, we examine the role of hegemony in relation to the co-option of SEA literature and sustainability in the Brazilian context by the logic of development for economic growth in emerging economies. The methodological approach adopts a post-structural perspective that reflects Laclau and Mouffe’s discourse theory. The study employs a hermeneutical, rhetorical approach to understand and classify 352 Brazilian research articles on SEA. We employ Brown and Fraser’s (2006) categorizations of SEA literature to help in our analysis: the business case, the stakeholder–accountability approach, and the critical case. We argue that the business case is prominent in Brazilian studies. Second-stage analysis suggests that the major themes under discussion include measurement, consulting, and descriptive approach. We argue that these themes illustrate the degree of influence of the hegemonic politics relevant to emerging economics, as these themes predominantly concern economic growth and a capitalist context. This paper discusses trends and practices in the Brazilian literature on SEA and argues that the focus means that SEA avoids critical debates of the role of capitalist logics in an emerging economy concerning sustainability. We urge the Brazilian academy to understand the implications of its reifying agenda and engage, counter-hegemonically, in a social and political agenda beyond the hegemonic support of a particular set of capitalist interests.