Surveys are one of the most important tasks to be executed to get valued information. One of the main problems is how the data about many different persons can be processed to give good information about their environment. Modelling environments through Artificial Neural Networks (ANNs) is highly common because ANN’s are excellent to model predictable environments using a set of data. ANN’s are good in dealing with sets of data with some noise, but they are fundamentally surjective mathematical functions, and they aren’t able to give different results for the same input. So, if an ANN is trained using data where samples with the same input configuration has different outputs, which can be the case of survey data, it can be a major problem for the success of modelling the environment. The environment used to demonstrate the study is a strategic environment that is used to predict the impact of the applied strategies to an organization financial result, but the conclusions are not limited to this type of environment. Therefore, is necessary to adjust, eliminate invalid and inconsistent data. This permits one to maximize the probability of success and precision in modeling the desired environment. This study demonstrates, describes and evaluates each step of a process to prepare data for use, to improve the performance and precision of the ANNs used to obtain the model. This is, to improve the model quality. As a result of the studied process, it is possible to see a significant improvement both in the possibility of building a model as in its accuracy.

As the population’s demand for food continues to increase, aquaculture is positioned as a productive activity that provides high-quality protein. Aquaculture activity is characterized by its socio-economic impact, the generation of jobs, its contribution to food, and constant growth worldwide. However, in the face of threats of competition, producers must quickly adapt to market needs and innovate. Given this, this research aims to analyze the impact of the knowledge absorption capacity with the adoption of innovations by aquaculture producers in the Mezquital Valley in Hidalgo, Mexico. The methodological strategy was carried out through structural equation modeling using partial least squares and correlation tests. The findings show that knowledge absorption capacities explain 77.8% of the innovations carried out in aquaculture farms. Both variables maintain a medium-high correlation; the more significant the absorption capacity, the greater the innovation.

Despite its leading role in the urban transport system, paratransit is accused of being unsustainable and hostile to modernity. The reform of the sector is necessary in the context of the modernization of the transport system of African cities. It requires the formalization of actors through technical and financial support such as fleet renewal projects. This article attempts to analyze the financing process and the level of formalism of the operators constituted within the AFTU in the context of the financing operation of paratransit operators in Dakar, Senegal. The methodological approach adopted is based on the analysis of qualitative data from questionnaire surveys carried out in the AFTU network in Dakar; official documents¹ were also used. The results show that the Dakar financing model put in place has made it possible to make significant progress in the reorganization of paratransit professionals. In addition to the concessioned lines, a salaried system was introduced, pricing is now official and the standardized ticketing system has been put in place. Nevertheless, improvements are expected on the working conditions of employees, the capacity building of actors and the evolution of the legal status of companies.

The aim of this paper is to introduce a research project dedicated to identifying gaps in green skills by using the labor market intelligence. Labor Market Intelligence (LMI). The method is primarily descriptive and conceptual, as the authors of this paper intend to develop a theoretical background and justify the planned research using Natural Language Processing (NLP) techniques. This research highlights the role of LMI as a tool for analysis of the green skills gaps and related imbalances. Due to the growing demand for eco-friendly solutions, there arises a need for the identification of green skills. As societies shift towards eco-friendly economic models, changes lead to emerging skill gaps. This study provides an alternative approach for identification of these gaps based on analysis of online job vacancies and online profiles of job seekers. These gaps are contextualized within roles that businesses find difficult to fill due to a lack of requisite green skills. The idea of skill intelligence is to blend various sources of information in order to overcome the information gap related to the identification of supply side factors, demand side factors and their interactions. The outcomes emphasize the urgency of policy interventions, especially in anticipating roles emerging from the green transition, necessitating educational reforms. As the green movement redefines the economy, proactive strategies to bridge green skill gaps are essential. This research offers a blueprint for policymakers and educators to bolster the workforce in readiness for a sustainable future. This article proposes a solution to the quantitative and qualitative mismatches in the green labor market.

In recent years, the environment in the manufacturing industry has become strongly competitive, which is why companies have found it necessary to constantly adjust their strategies and take actions aimed at improving their performance and competitiveness in a sustainable way to grow and remain in the market. Therefore, this paper aims to present an analysis to explain the current situation in the manufacturing industry in Aguascalientes, Mexico, by means of a survey in which product eco-innovation (PEI), process eco-innovation (PrEI) and organizational eco-innovation (OEI) and its effect on environmental performance (EP) and sustainable competitive performance (SCP) were measured. The results show that (EP) is positively and significantly influenced by (PEI) and (PrEI), while no significant influence is found for (OE). Furthermore, it is confirmed that environmental performance positively and significantly influences (SCP). The findings obtained from this study point to the relevance of promoting eco-innovation activities in the manufacturing sector, as this will ensure sustainable competitiveness.