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This study addresses the COVID-19 infection and its relationship with the city’s constructive intensity, commuting time to work and labor market dynamics during the lockdown period.

Microdata from formal workers in Recife was used to adjust a probability model for disease contraction.

The authors' results indicate that greater distance to employment increases the probability of infection. The same applies to constructive intensity, suggesting that residences in denser areas, such as apartments in buildings, condominiums and informal settlements, elevate the chances of contracting the disease. It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others. The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

The research shows important causal relationships, making it possible to think about public policies for the health of individuals both when commuting to work and in living conditions, aiming to control contagion by COVID-19.

The lockdown effectively reduced contagion by limiting people’s mobility during the specified period.

It is also observed that formal workers with completed higher education have lower infection risks, while healthcare professionals on the frontlines of combating the disease face higher risks than others.

The authors identified positive and significant relationships between these urban characteristics and increased contagion, controlling for neighborhood, individual characteristics, comorbidities, occupations and economic activities.

The behavioural theory adds a new paradigm of analysis with the assumptions of the decision maker’s cognitive biases and their repercussions on financing decisions. The aim of the study is to analyse the repercussions of these biases on the adjustment speed of firm’s capital structure toward the optimal level.

Based on a partial adjustment model, the study uses the Dynamic Panel Fractional estimator to analyse panel data from 4,990 Portuguese entrepreneurial firms.

The results show that the cognitive overconfidence bias impacts the entrepreneurial firm’s capital structure. In fact, the firms run by overconfident managers adjust more slowly than their counterparts. Furthermore, the findings suggest that entrepreneurial firms make relatively fast adjustments toward the optimal debt level and follow a hierarchical financing order in the funding process.

The results of this paper are not only interesting to the academia, but also contain practical implications for corporate, institutional and business policy and governance. First, the paper introduces a new measure of cognitive bias in optimistic managers, which is useful for current and future academic research. Also, in practical terms, the findings of the paper reveal that when a company is contemplating hiring a manager, it should consider whether they need an optimistic or non-optimistic manager based on the company's present life cycle or situation.

The current analysis extends the existing literature. The study suggests that financial classical and behavioural paradigms should not be separated, which can provide evidence to help narrow the gap between these two major perspectives.

The paper aims to present a literary itinerary inspired in Julio Dinis’ novel An English Family (Uma Família Inglesa) through a comparative analysis of the places identified in the novel and the touristic attraction proposed by Visit Porto website. This novel is representative of the cultural identity and society of Porto city in the 19th century. Developing an itinerary based on this novel can facilitate the reading and understanding of the historical and cultural development of Porto.

This case study is based on the reading of the Julio Dinis’ novel An English Family (Uma Família Inglesa), whose storyline takes place in Porto city, Portugal in the 19th century. It used QGIS v. 3.12 software, a geographical information system to identify the places, to produce the maps and to create the itinerary.

The comparison between the places identified in the novel and the tourist attraction in Visit Porto website revealed that only 6 points in the novel are referenced on Visit Porto website. These points correspond to the ones in the historical city centre of Porto. However, the creation of an itinerary that brings together all the points mentioned by Julio Dinis in his novel, will allow the development of a new touristic itinerary, alternative to existing itineraries in the city and that can be seen as a distinguish offer that allows a different view of the urban space of Porto.

There are some limitations to this study that can be highlighted. First, it was difficult to find the correct location of some points identified in the novel, due to difficulty of finding historical maps with quality of the data. At the same time, as tourist information is dispersed by several sources, and most of those data is not georeferenced, it was time consuming the integration of all the information in the same geodatabase. The choice of the shortest path can also be considered as a limitation, rather than the route followed by the author in the novel, but geographic information systems operates on spatial and temporal scale, which can present a limitation in tourism analysis. In the case of this project, we have chosen the shortest path, assuming that tourist would prefer that.

This research allowed to address two areas of knowledge that are emerging in the study of urban centres as tourist areas: the use of GIS and literary tourism. Despite the fact that there are already articles on this subject, the originality focuses on the approach made around one of the greatest writers of Portugal in the 19th century, allowing to present a tourist itinerary about one of his literary works, and the comparison made between the places identified in the novel and the tourist points identified on the Visit Porto website.

This study aims to explore how manufacturing firms master customer lock-in through value creation by servitization innovation strategies from the perspective of asset specificity.

A multiple case study with triangulation fashion is adopted to identify servitization innovation strategies. Several manufacturing firms were investigated, which are distributed in different positions of the value chain. Content analysis and abductive approaches are adopted to analyze the data. Moreover, an in-depth interview and participatory observation were conducted to refine the analysis results.

This study identified four different focusing points of servitization operations. Based on these, the paper further induces an innovative servitization strategy matrix of customer lock-in, concerning communion, intellectual, existential and insubstantial strategies. Furthermore, a conceptual model of customer lock-in by servitization innovation from the perspective of asset specificity is elaborated. It is suggested that companies can use tangible or intangible resources by sharing or storing operations to create servitization value.

This study theoretically proposes a conceptual model to extend servitization innovation as an intangible asset and adopt the new perspective of asset specificity to illustrate the value creation in servitization to generate customer lock-in.

The Spain–Portugal Cross-Border Cooperation Program launched the “Espomar” project in 2017, with the aim of designing a sustainable and transboundary maritime transport system in the Gulf of Cádiz, which includes the Spanish provinces of Cádiz (its Atlantic coast) and Huelva, together with the Portuguese region of the Algarve. This chapter limits the scope to the Algarve-Huelva connection and the resident population demand. The findings suggest a maritime connection defined and marketed as part of leisure activities. The demand for potential tourism packages created around boat trips appears to be promising. The sun beach, gastronomy wine and culture landscape vectors are the main attractors.

The present research aims to understand how the literature on lean leadership is currently structured. For this, the thematic subdivisions within the subject (thematic clusters) are analyzed as well as the networks between authors and the authors' countries and the chronological co-occurrence of terms over the years.

The research strategy chosen was a bibliometric analysis conducted with documents collected from the Scopus scientific database. After screening, 192 documents were analyzed using the Vosviewer software.

The main result is related to identifying four thematic clusters. The first cluster is connected to the manufacturing and supply chain industry, and this showed an increasing concern with sustainability, agile manufacturing and digitalization. The second is related to small and medium-sized companies in which Lean concepts, often associated with Six Sigma ideas, present as differentials for competitive advantage. The third one is associated with the civil construction segment, in which there is a great need for cultural and organizational change. The fourth cluster focuses on health organizations. In all clusters, leadership plays a key role.

Besides the contributions to the literature on the theme, this study provides interesting insights for managers regarding the path the managers' sectors are taking in the Lean leadership context.

There are no studies that critically examine Lean leadership literature. This research identifies clusters on the theme, showing how Lean leadership is being addressed by international research.

This study aims to examine how the adoption of digital technologies affects the business competitiveness of countries in Latin American and European countries.

This study used a structural model based on factors representing the pillars of the Global Competitiveness Index: financial system, adoption of information and communication technologies (ICT), skills, labor market, product market, macroeconomic stability, business dynamism and gross domestic product (GDP) purchasing power parity (PPP) as a percentage of the total world value. The authors considered 17 Latin American and 28 European countries. The model was analyzed by partial least squares-structural equation modeling.

ICT adoption in Latin American countries is a strong predictor of business dynamism (66% of the variance), skills (81% of the variance), product market (75% of the variance), labor market (42% of the variance) and financial system (49% of the variance). Similarly, ICT adoption in European countries is a strong predictor of business dynamism (35.6% of the variance), skills (72.2% of the variance), product market (51.6% of the variance), labor market (81.7% of the variance, but with a negative path coefficient) and financial system (38% of the variance).

Latin American countries should create policies to build skills to increase ICT adoption, and improve business and labor market dynamism. A theoretical implication is that the authors propose two structural models based on the GCI that best explains competitiveness in Europe and Latin America.

Using GCI data, the authors present empirical evidence on the predictors of competitiveness across 17 Latin American and 28 European countries with a special focus on the adoption of digital technologies.

The scientific community shares a heritage of knowledge generated by several different fields of research. Identifying how scientific interest evolves is relevant for recording and understanding research trends and society’s demands.

This article presents SciBR-M, a novel method to identify scientific interest evolution from bibliographic material based on Formal Concept Analysis. The SciBR-M aims to describe the thematic evolution surrounding a field of research. The method begins by hierarchically organising sub-domains within the field of study to identify the themes that are more relevant. After this organisation, we apply a temporal analysis that extracts implication rules with minimal premises and a single conclusion, which are helpful to observe the evolution of scientific interest in a specific field of study. To analyse the results, we consider support, confidence, and lift metrics to evaluate the extracted implications.

The authors applied the SciBR-M method for the Educational Data Mining (EDM) field considering 23 years since the first publications. In the digital libraries context, SciBR-M allows the integration of the academy, education, and cultural memory, in relation to a study domain.

Cultural changes lead to the production of new knowledge and to the evolution of scientific interest. This knowledge is part of the scientific heritage of society and should be transmitted in a structured and organised form to future generations of scientists and the general public.

The method, based on Formal Concept Analysis, identifies the evolution of scientific interest to a field of study. SciBR-M hierarchically organises bibliographic material to different time periods and explores this hierarchy from proper implication rules. These rules permit identifying recurring themes, i.e. themes subset that received more attention from the scientific community during a specific period. Analysing these rules, it is possible to identify the temporal evolution of scientific interest in the field of study. This evolution is observed by the emergence, increase or decrease of interest in topics in the domain. The SciBR-M method can be used to register and analyse the scientific, cultural heritage of a field of study. In addition, the authors can use the method to stimulate the process of creating knowledge and innovation and encouraging the emergence of new research.

There is a growing need for methodological plurality in advancing operations management (OM), especially with the emergence of machine learning (ML) techniques for analysing extensive textual data. To bridge this knowledge gap, this paper introduces a new methodology that combines ML techniques with traditional qualitative approaches, aiming to reconstruct knowledge from existing publications.

In this pragmatist-rooted abductive method where human-machine interactions analyse big data, the authors employ topic modelling (TM), an ML technique, to enable constructivist grounded theory (CGT). A four-step coding process (Raw coding, expert coding, focused coding and theory building) is deployed to strive for procedural and interpretive rigour. To demonstrate the approach, the authors collected data from an open-source professional project management (PM) website and illustrated their research design and data analysis leading to theory development.

The results show that TM significantly improves the ability of researchers to systematically investigate and interpret codes generated from large textual data, thus contributing to theory building.

This paper presents a novel approach that integrates an ML-based technique with human hermeneutic methods for empirical studies in OM. Using grounded theory, this method reconstructs latent knowledge from massive textual data and uncovers management phenomena hidden from published data, offering a new way for academics to develop potential theories for business and management studies.