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This paper aims to address what it means to brand a city as “smart”. In other words, what ideas, understandings and actions are mobilized by the discourse of smart cities in a particular context.

Taking a brand interpretive approach, this paper uses deconstructive criticism to understand the performativity of smart cities within the Brazilian Charter for Smart Cities and to expose hegemonic power structures and the various colonizations that disenfranchise consumers and citizens of the Global South.

This paper finds that the branding of smart cities within the Brazilian Charter for Smart Cities is largely performative and rhetorical in nature. The authors identify those dimensions of the smart city that are materialized by this branding performance. For example, the authors identify how the Charter calls forth issues around technological solutionism, sustainability and social inclusion. At the same time, the analysis draws attention to the dimensions of smart cities that are disguised by such performances.

The implications of the work suggest that the authors need to understand the designation “smart city” as a branding performance. More research is required in context to determine in exactly what ways smart city projects are being implemented.

Rather than adhering only to the rhetoric of smartness, cities have to work hard to make smartness a reality – a smartness constructed not just on technical solutions but also on human solutions. That is, the complexity of urban issues that are apparently addressed in the move to smartness demand more than a technological fix.

The research offers a novel lens through which to view smart cities.

A review of the literature provides a solid reason to believe that an increase in environmental, social and corporate governance (ESG) activities have a positive impact on banks’ default risk (DR). However, the increasing impact of climate risk on credit, operational and market risks, as well as the reduced availability of funding for banks that underperform in terms of ESG risk, is a concern. Therefore, the purpose of this study is to verify the relevance of the implementation of ESG policies to a bank’s DR, against the background of macroeconomic and bank-specific factors.

Using a data set of 303 commercial banks from 61 countries from 2012 to 2021 and a panel regression methodology, the empirical importance of ESG activities for bank DR is documented. The two-stage generalized method of moments estimator was used to test the research questions.

Comparing different factors, the results highlight the positive impact of ESG activities on the bank’s DR. However, this relationship varies according to the specific pillars of the bank’s sustainability policies and changes into negative ones.

This paper fits the domain of DR management research, investigating whether ESG performance affects bank DR while controlling macroeconomic and market drivers. Prior literature has shown evidence on the relationship between macro and market forces and a bank’s risk profile while a limited one on the non-market drivers. The main contribution is to consider ESG (in total and as separate pillars) as independent drivers of the bank risk profile.

This paper argues that past events of queer resistance – such as the Stonewall Riots in 1969 in New York – need to be critically inquired for their meaningful legacy and future potentiality through remembering and re-experiencing these events affectively. Considering the recent backlash against LGBTQI+ people, the paper underlines the importance of a nuanced understanding and affective remembering of historic events like the Stonewall riots for contemporary queer activism and scholarship.

The study engages with the analysis of a new opera production commissioned by the New York City Opera at the occasion of the 50th anniversary of the Stonewall riots. The focus of this uprise at and around the Stonewall Inn is seen as an emblematic event synonymous with what was then called “gay” liberation and forms a significant moment of collective troublemaking in queer history. Operas like other cultural performances are considered as forms of queer worldmaking, which can be analyzed as an evolving stream of ambivalent affect and minor feelings.

The paper offers an affective analysis of the performance of the opera “Stonewall.” First, the analysis provides a sketch of how individual storylines struggling with the ambivalence between daily humiliation and sexual longing assemble into a collective affective complex that layered the intensity of the uprising. Second, the analysis documents how the Stonewall-opera “re-members” the intersectional composition of these ambivalent affects to counter the tendency to mainstream queer history.

The paper’s writing illustrates how the collective organizing of queer resistance can be advanced through exploring such unusual aesthetic realms like queer opera, as it connects troublemaking politics with affective activism, the reviving of affective moments in queer history. It underlines the potential of queer opera and other cultural, popular productions to feel and live the intensity and energy of reimagining and realizing queer worldmaking.

This paper aims to evaluate the measurement properties of the Employee Perception to Assess the Lean Implementation Tool (EPLIT) in the Brazilian hospital context.

A cross-sectional study was conducted in two Brazilian hospitals, adhering to COnsensus-based Standards for the selection of health Measurement Instruments (COSMIN) guidelines. Exploratory factor analysis (EFA) and Cronbach's alpha were used for construct validity and reliability.

The adapted tool comprises 27 items across five domains, explaining 63.3% of the variance. Cronbach's alpha ranged from 0.78 to 0.86, indicating satisfactory reliability.

Limitations include convenience sampling and exclusive use of EFA for validation. Future studies may employ Confirmatory Factor Analysis for further validation.

The tool aids healthcare managers in Brazil to systematically evaluate Lean implementation, contributing to process optimization and quality improvement.

Effective Lean implementation using the validated tool could lead to improved healthcare delivery and patient outcomes.

This is the first study to adapt and validate EPLIT for the Brazilian healthcare sector, offering a robust tool for managers and researchers.

Integrated marketing communication (IMC) is a management tool that accompanies market dynamics, business environment and technological transformations and can become a competitive differential for organizations that use it. This study’s aim is to propose that IMC can be a strategic tool in the context of geographical indication (GI).

Exploratory research was conducted with a qualitative approach through an integrated unique case study, including bibliographic, documentary research, direct observation and in-depth semi-structured interviews. The case chosen was the GI of Matas de Rondônia coffee, located in the Amazonia biome, which is the first denomination in the world of the sustainable Coffea canephora species and, to date, Brazil’s only GI to include indigenous lands.

It was possible to confirm all propositions, and obtain theoretical, practical and public management contributions.

This research brings unpublished theoretical contributions, when presenting IMC as a strategic tool for GI, fills gaps and increases the literature in the areas of marketing, communication, food marketing and GI.

Social media platforms that disseminate scientific information to the public during the COVID-19 pandemic highlighted the importance of the topic of scientific communication. Content creators in the field, as well as researchers who study the impact of scientific information online, are interested in how people react to these information resources and how they judge them. This study aims to devise a framework for extracting large social media datasets and find specific feedback to content delivery, enabling scientific content creators to gain insights into how the public perceives scientific information.

To collect public reactions to scientific information, the study focused on Twitter users who are doctors, researchers, science communicators or representatives of research institutes, and processed their replies for two years from the start of the pandemic. The study aimed in developing a solution powered by topic modeling enhanced by manual validation and other machine learning techniques, such as word embeddings, that is capable of filtering massive social media datasets in search of documents related to reactions to scientific communication. The architecture developed in this paper can be replicated for finding any documents related to niche topics in social media data. As a final step of our framework, we also fine-tuned a large language model to be able to perform the classification task with even more accuracy, forgoing the need of more human validation after the first step.

We provided a framework capable of receiving a large document dataset, and, with the help of with a small degree of human validation at different stages, is able to filter out documents within the corpus that are relevant to a very underrepresented niche theme inside the database, with much higher precision than traditional state-of-the-art machine learning algorithms. Performance was improved even further by the fine-tuning of a large language model based on BERT, which would allow for the use of such model to classify even larger unseen datasets in search of reactions to scientific communication without the need for further manual validation or topic modeling.

The challenges of scientific communication are even higher with the rampant increase of misinformation in social media, and the difficulty of competing in a saturated attention economy of the social media landscape. Our study aimed at creating a solution that could be used by scientific content creators to better locate and understand constructive feedback toward their content and how it is received, which can be hidden as a minor subject between hundreds of thousands of comments. By leveraging an ensemble of techniques ranging from heuristics to state-of-the-art machine learning algorithms, we created a framework that is able to detect texts related to very niche subjects in very large datasets, with just a small amount of examples of texts related to the subject being given as input.

With this tool, scientific content creators can sift through their social media following and quickly understand how to adapt their content to their current user’s needs and standards of content consumption.

This study aimed to find reactions to scientific communication in social media. We applied three methods with human intervention and compared their performance. This study shows for the first time, the topics of interest which were discussed in Brazil during the COVID-19 pandemic.

The aim of this study is to perform a systematic literature review on retail agglomeration literature and present an agenda of future research in this domain.

To synthesize and evaluate the retail agglomeration literature, the study adopts a structured systematic literature review approach. Additionally, the study employs the Theory-Context-Characteristics-Methodology (TCCM) framework to present future research directions in the retail agglomeration domain.

This review proposes a conceptual framework showing the relationships between the antecedents, mediators and consequences reported in the retail agglomeration literature. Lexicometric analysis shows that the key themes of retail agglomeration research are retail store selection and retail performance, retail location strategy and store format, customer perceptions, behavior and expectations.

Specific criteria used for the inclusion of literature limits articles considered for the current systematic review. Also, only those articles published in English were considered.

Based on the proposed model, this review presents strategies to enhance the performance of retail agglomeration.

This study has systematically synthesized the retail agglomeration literature to explore its development over time and proposes a research framework which provides a comprehensive understanding of retail agglomeration literature.

This article examines the influence of market opportunity, risk, and distance on the choice of destination country for Mexican franchises.

The research hypotheses are developed under the theoretical approaches of institutional theory, agency theory, and transaction costs theory and were contrasted on the data obtained from 52 Mexican international franchisors operating in 37 countries as of 2016. This study uses linear regression with ordinary minimums using the STATA 13.1 software.

The results reveal that a larger market size, a greater level of economic freedom, and a smaller geographic distance are determining factors in the choice of destination country. No statistical significance was found in the variables GDP per capita, level of democracy and cultural distance.

This research contributes to the theoretical and practical field. On the theoretical side, this study integrates institutional theory, agency theory, and transaction cost theory to evaluate the factors of the destination country that influence the internationalization process of the franchise. Another contribution of this study is to apply theories and models of developed economies to the process of internationalization of franchises in an emerging economy. Additionally, this study is based on a model that considers the distance, opportunities and risks that are considered by Mexican franchisors in the selection of the international markets in which they maintain operations. This study contains important practical implications that can serve as relevant information for decision-making in the franchise sector and its internationalization. This data is valuable for new models of Mexican franchises that decide to start their internationalization process.

This study explores previous research related to textile management technologies, detecting gaps and opportunities for textiles made by Ainu people. We also propose an approach to digitally read Ainu textile patterns.

We employed indigenous and pluriversal design frameworks to evaluate textile pattern technologies. They were operationalised as Indigenous/local researchers involved in the investigation, multi-sensoriality of analysed items, prosperity for everyone involved, communal property of data, biological awareness, social complexity awareness and sensitivity of the analysed method if the items change.

Textile pattern technology researchers have mostly used neural networks and clustering methods. They have addressed social aspects since the 2000s. Investigations into the generation of textiles based in Poland constantly reflected the most pluriversal characteristics. Regarding Ainu textile research, most investigations have cited Indigenous sources. Two gaps emerged: the concentration of research datasets and results in enterprises or scholars and the focus on the formal characteristics of Ainu patterns in technical papers and contextual characteristics in ethnographic papers.

Heritage management is increasingly employing technological tools that should consider the sustainability of handmade/artisanal goods. As most investigations on textile patterns are conducted by the industry, their benefits are limited for heritage conservation.

Therefore, we suggest digital experts work together with ethnography and Indigenous experts, proposing a method for digital reading of Ainu textile patterns that incorporates pluriversal aspects into heritage conservation.

Pluriversal design is a set of onthologies proposed with Indigenous, mestizo and minorities from the Americas that is currently being diffused in the rest of the world, highly compatible with the analysis of Indigenous heritage.

The purpose of this paper is to systematically analyze the literature around regulatory compliance and market manipulation in capital markets through the use of bibliometrics and propose future research directions. Under the domain of capital markets, this theme is a niche area of research where greater academic investigations are required. Most of the research is fragmented and limited to a few conventional aspects only. To address this gap, this study engages in a large-scale systematic literature review approach to collect and analyze the research corpus in the post-2000 era.

The big data corpus comprising research articles has been extracted from the scientific Scopus database and analyzed using the VoSviewer application. The literature around the subject has been presented using bibliometrics to give useful insights on the most popular research work and articles, top contributing journals, authors, institutions and countries leading to identification of gaps and potential research areas.

Based on the review, this study concludes that, even in an era of global market integration and disruptive technological advancements, many important aspects of this subject remain significantly underexplored. Over the past two decades, research has lagged behind the evolution of capital market crime and market regulations. Finally, based on the findings, the study suggests important future research directions as well as a few research questions. This includes market manipulation, market regulations and new-age technologies, all of which could be very useful to researchers in this field and generate key inputs for stock market regulators.

The limitation of this research is that it is based on Scopus database so the possibility of omission of some literature cannot be completely ruled out. More advanced machine learning techniques could be applied to decode the finer aspects of the studies undertaken so far.

Increased integration among global markets, fast-paced technological disruptions and complexity of financial crimes in stock markets have put immense pressure on market regulators. As economies and equity markets evolve, good research investigations can aid in a better understanding of market manipulation and regulatory compliance. The proposed research directions will be very useful to researchers in this field as well as generate key inputs for stock market regulators to deal with market misbehavior.

This study has adopted a period-wise broad-based scientific approach to identify some of the most pertinent gaps in the subject and has proposed practical areas of study to strengthen the literature in the said field.