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The purpose of this study is to examine the mediating role of manufacturing flexibility in the relationship between knowledge creation, technological turbulence and performance. In an increasingly competitive and changing environment, firms need to boost their technological and management know-how to adequately develop manufacturing flexibility.

This study analyzes survey data collected from 370 manufacturing firms. Validity and reliability analyses were conducted using SPSS and Amos. The research hypotheses were tested using covariance-based structural equation modelling.

The main findings show that knowledge creation positively and significantly affects business and operational performances directly, and indirectly, through manufacturing flexibility. Moreover, technological turbulence has a positive and significant effect on it. This finding contributes to understanding why some firms get better outcomes from manufacturing flexibility than others, a disputed issue in the literature.

This study highlights the need for manufacturing firms to foster cultures of knowledge creation, to better educate and train employees and to develop other instruments of knowledge creation.

This study makes several contributions to manufacturing flexibility literature: (1) establishing a link between technological turbulence and knowledge creation to develop manufacturing flexibility; (2) add empirical evidence on the relation between manufacturing flexibility and performance and (3) contributes to consolidating the mediation role of manufacturing flexibility in the relations between knowledge creation and business performance, as studies focussing on such a role are scarce in the literature.

This paper aims to explore the characteristics of capability exchange within internationalizing small and medium enterprises (SMEs) of the Portuguese metallurgic and metal-mechanic sectors.

Multiple case research instrumentalizes a (manifest) content analysis based upon qualitative data gathered from the interviewing of the strategic apex of four multinational enterprises, codified in the light of the well-known Weber protocol.

The results uncover the existence of a multi-diffusional approach with a bi-directional regime of transferability, where reciprocal transference is non-simultaneous. Operational rigidities are asserted to be stifling the diffusion of capabilities across subsidiaries and hindering higher economies of learning.

The current paradigm of international capabilization of the sector requires substantial enhancements in its design for the benefit of the firm’s international competitiveness, growth and wealth.

Organizational capabilities are a determinant of competitiveness. Hitherto, the phenomena of (capabilities) mobility and transferability are still acknowledged as a clear gap. This study opens, therefore, avenues on international capabilization in relation to the modeling and testing of global dynamic capabilities and its replicability across industries.

Dynamic capabilities yield positive effects to firm-specific advantage formation. Paradoxically, the body of literature on capability diffusion is scarce. The purpose of this study is to focus, thus, on this dearth of literature with an emphasis on exploring the transferability function.

An integrative review of literature on the dynamic capabilities view covers the organizational context determining capability sharing, supported by strategic communication and business networking theories for the fashioning of global capabilities’ administration model (GCAM).

Individual motivations and formal modelling of capabilities’ transference have been overlooked in previous research. Largely with a top-down orientation, the current paradigm of their diffusion is profoundly shaped by the organizational structure and its global governance practices.

The GCAM’s architecture, based on transnational administration and hybrid transferability, opens horizons for multinational companies to develop their own capability management systems and is at the same time a new scholarly avenue in the field.

This study explores an untapped research gap and the formal modelling of a GCAM, while reconciling some of the weaknesses of academic research and industry practices.

Maintenance represents an indispensable role in the productive sector of the steel industry. The increasing use of operating with a high level of precision makes hydraulic systems one of the issues that require a high level of attention. This study aims to explore an empirical investigation for decreasing the occurrences of corrective maintenance of hydraulic systems in the context of Lean 4.0.

The maintenance model is developed based on action-research methodology through an empirical investigation, with nine stages. This approach aims to build a scenario to analyze and interpret the occurrences, seeking to implement and evaluate the actions to be performed. The undertaken initiatives demonstrate that this approach can be applied to optimize the maintenance of an organization.

The main contribution of this paper is to demonstrate that the applied method allows the overviewing results, with a qualitative approach concerning the maintenance actions and management processes to be considered, allowing a holistic understanding and contributing to the current literature. The results also indicated that Lean 4.0 has direct and mediating effects on maintenance performance.

This research intends to propose an evaluation framework with an interdimensional linkage between action research methodology and Lean 4.0, to explore an empirical investigation and contributing to understanding the actions to reduce the occurrences of hydraulic systems corrective maintenance in a production line in the steel industry.

This paper aims to clarify the relationship between foreign direct investment (FDI), democracy and carbon intensity. This study examines the influence of types of democracy on the relationship between inward FDI and carbon intensity. For this purpose, it uses five varieties of democracy, including a composite democracy indicator as moderating variables.

This study applies the fixed-effects panel quantile regression approach that considers unobserved heterogeneity and distributional heterogeneity using panel data from 160 countries during 1990–2020. By taking into account sudden changes in the volume of inward FDI, an event study is conducted across various sub-samples of democracy to check the robustness of the results.

The results show that FDI has a significantly negative impact on carbon intensity of the host country in the upper quantiles. In general, different types of democracy have a significant positive impact on carbon intensity across different quantiles. After considering the other factors, including industry intensity, trade openness, green technology, fossil fuel dependency and International Environmental Agreements, there is evidence that all types of democracy moderate the relationship between FDI and carbon intensity, thereby supporting the halo effect hypothesis. In addition, the interaction effects have a significant negative impact on carbon intensity of low- and high-carbon-intensive countries.

This paper offers several contributions to the literature on the effect of FDI and democracy on carbon intensity. This study overcomes the limitations related to the conceptualization and measurement of democracy found in the literature. While prior research has predominately concentrated on how democracy promotes the selection of FDI host-country locations, this study seeks to answer the question of whether democracy type has any effect on inward FDI, thus contributing to improving carbon intensity. Furthermore, this paper analyses the interaction effect on carbon intensity in different countries with different carbon intensity levels separately.

Up-to-date, the simulation of pedestrian behavior is used to support the design and analysis of urban infrastructure and public facilities. The purpose of this paper is to present a microscopic model that describes pedestrian behavior in a two-dimensional space. It is based on multi-agent systems and cellular automata theory. The concept of layered-intelligent terrain from the video game industry is reused and concepts such as tracing, evasion and rejection effects related to pedestrian interactive behavior are involved. In a simulation scenario, an agent represents a pedestrian with homogeneous physical characteristics such as walking speed and height. The agents are moved through a discrete space formed by a lattice of hexagonal cells, where each one can contain up to one agent at the same time. The model was validated by using a test that is composed of 17 real data sets of pedestrian unidirectional flow. Each data set has been extracted from laboratory-controlled scenarios carried out with up to 400 people walking through a corridor whose configuration changed in form of the amplitude of its entrance doors and the amplitude of its exit doors from one experiment to another. Moreover, each data set contained different groups of coordinates that compose pedestrian trajectories. The scenarios were replicated and simulated using the proposed model, obtaining 17 simulated data sets. In addition, a measurement methodology based on Voronoi diagrams was used to compute the velocity, density and specific flow of pedestrians to build a time-series graphic and a set of heat maps for each of the real and simulated data sets.

The approach consists of a multi-agent system and cellular automata theory. The obtained results were compared with other studies and a statistical analysis based on similarity measurement is presented.

A microscopic mobility model that describes pedestrian behavior in a two-dimensional space is presented. It is based on multi-agent systems and cellular automata theory. The concept of layered-intelligent terrain from the video game industry is reused and concepts such as tracing, evasion and rejection effects related to pedestrian interactive behavior are involved. On average, the simulated data sets are similar by 82 per cent in density and 62 per cent in velocity compared to the real data sets. It was observed that the relation between velocity and density from real scenarios could not be replicated.

The main limitations are presented in the speed simulations. Although the obtained results present a similar behavior to the reality, it is necessary to introduce more variables in the model to improve the precision and calibration. Other limitation is the dimension for simulating variables at this moment 2D is presented. So the resolution of cells, making that pedestrian to occupy many cells at the same time and the addition of three dimensions to the terrain will be a good challenge.

In total, 17 data sets were generated as a case study. They contain information related to speed, trajectories, initial and ending points. The data sets were used to calibrate the model and analyze the behavior of pedestrians. Geospatial data were used to simulate the public infrastructure in which pedestrians navigate, taking into account the initial and ending points.

The social impact is directly related to the behavior analysis of pedestrians to know tendencies, trajectories and other features that aid to improve the public facilities. The results could be used to generate policies oriented toward developing more consciousness in the public infrastructure development.

The general methodology is the main value of this work. Many approaches were used, designed and implemented for analyzing the pedestrians’ behavior. In addition, all the methods were implemented in plug-in for Quantum GIS. The analysis was described with heat maps and statistical approaches. In addition, the obtained results are focused on analyzing the density, speed and the relationship between these features.

The aim of this article is to analyse the opinions (and the differences among them) of golf players, golf courses managers and the general population about the economic and social impact of golf courses in a tourist destination (Alicante province, in Spain) from the data collected in three surveys. Golf players and golf courses managers have a more positive opinion about this economic and social impact than the population in the province. This is due to the knowledge of the first group about golf industry benefits. Therefore, communication about these social and economic benefits of golf courses has to be increased with the population in the area in order to improve their opinion about them.

This paper aims to compare the efficiency of spatial and nonspatial hedonic price models in capturing housing submarkets dynamics for cities in developing countries. This study expects to contribute to a better understanding of the housing price determinants from both nonspatial and spatial perspectives. In addition, this paper fills a gap in the literature on the study of housing prices from a spatial perspective in Latin American cities.

This study uses a comparative analysis between an ordinary least squares regression and a geographical weighted regression, GWR. The study also assesses the performance of two distinct data sources: the city’s cadastral records and a real estate sales web portal.

The results suggest that compared to the traditional regression model, the spatial regression models are more effective at capturing housing market variations on a fine scale. Moreover, they reveal interesting findings on the spatial varying, sometimes contradictory effects of some housing attributes on housing prices in different areas of the city, suggesting the potential impact from segregation.

The availability of data on housing prices and characteristics in Latin American cities is fragmented and complex. The level of detail, granularity and coverage is not consistent over time. For this reason, this study combines and compares data sets from official and unofficial sources in an effort to close this gap. Likewise, the socioeconomic variables that come from the census must be carefully analyzed, knowing the historical context in which they were constructed, what they represent and their interpretation.

This paper suggests that despite the improvement on the spatial models, the selection of a specific one should always be based on the diagnosis of it as it highly depends on the data used and the objectives of the study.

This study enriches the limited body of literature on spatial hedonic price models of housing in Latin American cities. It also shed light on the importance of spatial approaches to identify complex housing submarkets.