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The article's objective is to analyze the consequent factors of Big Data Analytics Capability for firms in the competitive scenario, using different analytical models.

The research had a quantitative approach, using a survey of data from firms located in the state of São Paulo – Brazil. Structural Equation Modeling (SEM) was used to validate the model.

The results reveal that all hypotheses were accepted. Business value was the construct that had the most explanatory power in the model. It is necessary to invest more in analytical tools, as well as people trained in the analysis of these models, in addition to a change of mindset, which will dictate the bias of the firm's strategic decision-making. The Big Data analysis is evident from firms' growing investments, particularly those that operate in complex and fast-paced environments.

The proposed theoretical model makes it possible to verify firms' analytical structure and whether they are better positioned to analyze customer data and information in real-time, generate insights and implement solutions to maintain and improve their market position.

The contribution of this article is to present a proposal to expand the research models in the literature that analyzed the direct and indirect relationship between “Big Data Analytics Capability” and “Product Innovation Performance”.

This study aims to investigate the effects of nomophobia in the organizational environment, and the authors developed a research model consisting of the construct's loneliness, depression and anxiety. The growing competitiveness of the market and the need of many companies regarding the availability of employees demand attention.

The authors surveyed 454 Brazilian respondents and used covariance-based structural equation modeling to analyze the survey results. The model’s hypotheses proved significant, confirming the relationships proposed by the theoretical model.

Loneliness and depression, rather than anxiety, explained the influence of nomophobia on individuals’ ability to communicate when inserted in the professional context. Individuals were most likely to have high nomophobia incorporate psychological traits that involve emotional instability, and could benefit from the connection between people in a social group.

This study confirms that nomophobia can be a situational phobia evoked by the unavailability of a smartphone or by the idea of not having it, not being able to use it or losing it, even within the business context.

The increase in loneliness and depression indicates a deficiency in the face of the smartphone’s benefits.

This paper provides contributions that seek to understand the effect of symptoms from smartphones in the workplace, also indicating that users may cause vulnerability. Companies can prevent vulnerability by creating policies prohibiting their use in the organization’s context and developing healthy habits that do not lead to addiction.

The purpose of this paper is to identify the intention of living in a smart city as from its characteristics in the individual perception by the young public based on the proposal of an expanded model.

The empirical research carried out herein was based on a survey, consisting of a sample of 380 valid questionnaires. Data analysis was carried out through multivariate quantitative approach using structural equation modeling, with estimation by partial least square.

In the model, it was possible to adapt all the characteristics of smart cities. The “environment” characteristic was the one that presented the greatest relationship in contributing to efficiencies that allow the migration of citizens and in reducing the environmental impact in the cities’ quality, and the “economy” characteristic was the one that presented the lowest relationship opening the opportunity that this concept can be more widespread within the economic agents and individuals for the society.

Finally, it is argued that efficiency in all characteristics will depend on the engagement of citizens in the innovation processes of public living in general. The smart city is distinguished from other typologies due to its success in the field of innovation, essentially depending on the collaborative process that is developed in environments that encourage discovery and idea generation.

This research sought to propose a theoretical model that analyzes the factors associated with unlearning (individual and organizational) and contributes to generating and realizing ideas among young people at the beginning of their careers based on the predominant type of structure.

The study had a sample (n = 971) and used the multivariate data analysis partial least squares - Structural Equation Modeling (PLS-SEM regular) and multigroup analysis (PLS-MGA) to identify significant differences between the estimates of the specific parameters of each group (a- Organic/b- Mechanistic).

All the direct relationships and formulated mediations were found to be supported, except for H6 (ET→EO) within the group that had a primarily mechanistic organizational structure. Thus, the more turbulent the environmental, the more initiative-taking, innovative and risk-taking a company tends to be. However, it remains to be seen whether the organizational structure plays a role in facilitating or hindering this relationship. H1 (IG→IR) indicates that predominantly organic organizations have a stronger and more consistent relationship with the knowledge developed through individual and organizational unlearning process. This knowledge contributes to the idea-generation process and ultimately leads to realizing those ideas.

The article contributes to literature by proposing an original and integrated theoretical model incorporating individual and organizational approaches to unlearning to understand the effect on idea generation and realization.

This research aims to propose the development of a model that identifies, in essential services, the determining factors affecting the technological advances offered by different smart technologies in supermarket retail channels that influence citizens' quality of life, amidst the coronavirus disease 2019 (COVID-19) pandemic.

The data were collected using a cross-sectional questionnaire survey (n = 469). The authors applied the structural equation modeling (SEM) technique to test the hypotheses, along with the partial least squares (PLS) method for estimating latent variables and combining with the necessary condition analysis (NCA) method.

According to the results of the NCA method, the results were adequate, and more attention should be paid to the quality of life construct after finding the bottleneck point of 50%. In this sense, adaptive resilience was characterized as the main necessary predictor construct for quality of life. In addition, Generation Z and Millennials have the highest frequency of use in all smart technologies, with “assisted purchase” being the most widely used.

Finally, the effect of the pandemic changed the consumption routine with supermarkets, not being a mere option but a necessity in the context of a smart city.

As a result, the proposed model was consistent, showing that all direct and indirect SEM paths were validated, highlighting data security and privacy and resilience issues. In addition, the NCA method complemented the procedures performed in the SEM phase.

Education is undergoing digital transformation intensified by COVID-19. In this context, gamification is an attractive alternative based on the use of elements of the games with educational purposes. However, it keeps the educational content to be learned as a central element without neglecting the “fun,” which contributing to engaging students. Therefore, this study aims to analyze the factors that affect students' engagement in an undergraduate course of Business Administration with gamified activities in remote education.

The authors collected data through a survey available to students of the administration course at a private university in São Paulo (n = 671). This study used a quantitative approach, using SEM with PLS estimation and with the support of other analytical techniques.

The results support all the hypotheses formulated. Those with the associated construct “competition” obtained the most robust relationships, which denotes that competition is an essential element in gamification. Despite being supported by the results, “network exposure” influencing engagement is one point of attention to improving teaching strategies.

Graduate schools could implement this type of gamified activity, evaluating whether students enrolled in higher degrees would willingly engage in a learning activity considered “less serious.”

Higher education institutions can benefit from this study by understanding that gamification is presented as an active methodology that increases students' engagement in teaching.

This research addressed gaps in the factors that affect students' engagement with gamified activities, proposing an alternative theoretical model to those present in the literature.

The purpose of this paper is to provide a framework for radio frequency identification (RFID) technology adoption considering company size and five dimensions of analysis: RFID applications, expected benefits business drivers or motivations barriers and inhibitors, and organizational factors.

A framework for RFID adoption derived from literature and the practical experience on the subject is developed. This framework provides a conceptual basis for analyzing a survey conducted with 114 companies in Brazil.

Many companies have been developing RFID initiatives in order to identify potential applications and map benefits associated with their implementation. The survey highlights the importance business drivers in the RFID implementation stage, and that companies implement RFID focusing on a few specific applications. However, there is a weak association between expected benefits and business challenges with the current level of RFID technology adoption in Brazil.

The paper is not exhaustive, since RFID adoption in Brazil is at early stages during the survey timeline.

The main contribution of the paper is that it yields a framework for analyzing RFID technology adoption. The authors use this framework to analyze RFID adoption in Brazil, which proved to be a useful one for identifying key issues for technology adoption. The paper is useful to any researchers or practitioners who are focused on technology adoption, in particular, RFID technology.

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.

The purpose of this paper is to propose a process management framework for Chemical Waste Treatment Laboratories (CWTL) that can be used as a management tool to identify and manage critical process.

Proposition of a generic classification for categories of chemical waste; use of the ABC analysis as a tool for analysis of priority in relation to the inputs of an CWTL; use of the process matrix (variety vs volume) to identify the key resources required to perform the activities of a CWTL; and use of mapping process techniques to map the processes defined and calculate times.

The proposed framework was applied to a CWTL at University of São Paulo, Brazil, and showed that the high variability of demand is a significant factor in the management of this laboratory, requiring processes that are flexible to meet this demand. The results showed that the applicability of the production and operations management theories within the scope of process management of CWTLs, proved to be useful tools for improving the treatment efficiency of chemical waste in these facilities.

The novelty of this work is in the fact of using production and operations management tools in the management of CWTLs to propose diagnoses to improve the management of their processes. The proposition of a comprehensive classification for chemical wastes generated in CWTLs is also highlighted.

The Sertão, located in the Northeastern region of Brazil, is the most populous semi-arid region in the world. The region also faces the highest rates of poverty, food insecurity and climate risks in this country. Basic economic activities, such as extensive livestock and dairy farming, tend to be mainly affected by the increasing temperatures and recurrent droughts taking place in the past decades. This paper aims to analyze farmers’ responses to climatic variability in the Sertão.

Analyses are based on farm-level data of the Agricultural Census 2006 and on historical climate data gathered by meteorological stations. The climate impacts and the effectiveness of adaptive strategies are compared between three groups of farms, which discriminate different levels of social and environmental vulnerability. Four production functions are modeled (milk, cattle, goat and sheep) accounting for sample selectivity bias.

In response to increasing temperatures, farmers tend to shift their activities mainly to cattle and dairy farming. But the overall productivity tends to reduce with the recurrence of droughts. Decreasing precipitation affects mainly the production of milk of smallholder family farmers and the cattle herd of non-family farmers.

Analyses do not account for short- and medium-run productive impacts of extreme droughts, which usually have devastating socioeconomic effects in the region.

Smallholder family farmers are the most vulnerable group who deserve more social and technical intervention, as they lack basic social and technological resources that can greatly improve their productivities and overcome the impacts of decreasing precipitation.