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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.

This chapter presents a combined approach of social and open data to evaluate a hybrid education model with online and face-to-face classes. The study consists of a sample of 310 students from the UPIITA-IPN college. Thus, a grouping model was applied based on each student's profile and academic performance in various subjects to identify patterns and learning styles. In addition, a social sensor of emotions was implemented to measure reactions in online and face-to-face classes. It helped to identify which strategies and methods are most significant for student performance. Data were collected from forms and the Twitter social network, filtering data by general opinions about learning and experiences in class. Considering trends and patterns, we identified four types:

Pattern (1) personalization of learning: This group stood out because online teaching allows you to work at your own pace and on your own schedule. In addition, a trend toward a more individualized learning approach or the versatility of personalizing learning was observed. Pattern (2) an excessive number of channels and information: This group of students was characterized by feeling overwhelmed by the amount of information they must process in an online environment, in addition, to using various communication channels (messaging, Classroom, Zoom, Teams, email, among others) this was associated with a feeling of isolation and a lack of commitment. Pattern (3) inequality and asynchronous learning: Students with difficult access to adequate resources at home (connection, own computer, etc.). They were characterized by not being able to have the same performance in the different learning activities and expressed that the content must be adapted to the individual needs of the students. Technical problems, such as Internet connection failures or problems with electronic devices, interrupted the learning process and generated frustration for students and teachers. Pattern (4) lack of social interaction: This affected the student's ability to develop social and emotional skills. Moreover, it generates difficulties for the students to collaborate, slowing the development of social and emotional skills. It concluded that a hybrid model is successful, having schemes combined with 65% face-to-face sessions and 35% online.

In this chapter, we describe the challenge and experience to spread out information and communication technologies (ICT) and how to implement them progressively, in order to improve administrative, academic, and pedagogical issues. As a case study, institutional strategies to tackle these issues in the higher education institutions (HEI) that belong to the Instituto Politécnico Nacional of Mexico (IPN) are described. The main challenge of HEI to incorporate cutting-edge technology in order to form professionals according to educational models and needs of the worldwide is pointed out. Thus, the intended focus of this work is to elevate the discourse and generate awareness about information and communication technologies to translate the language for being legible and understandable to deans, directors, and general authorities of HEI so that they can clearly make decisions with respect to the benefits that current technologies bring to the education institutions, and thus they can keep in mind investing important economic resources in future and mature technologies. Nowadays, HEI of the IPN are facing problems regarding the allocation of budgetary resources, so the strategies and analytical discussion of how ICT can envision the growth of HEI is a very timely issue to be presented to the Mexican government.

Over the past few decades, the higher education landscape underwent dramatic changes, causing strain on higher education institutions (HEI) worldwide. The academic debate is filled with very well-argued accounts of these developments. Advances in information and communication technology (ICT) add an additional layer to this already complex reality. Against this backdrop, it is necessary that the question of managing and administering HEI today be rethought. Emerging technologies such as artificial intelligence (AI) and cognitive computing, augmented, virtual and mixed reality (R+), Internet of Things (IoT), blockchain, bear the promise to effectively assisting HEI administrators in navigating their institutions through the period of profound change. This chapter offers a brief account of that.

Consumer knowledge has been one of the most studied variables in marketing due to its strong influence on consumer behaviour. Knowledge level has traditionally been measured through objective knowledge and the number of correct answers in a battery of items about product characteristics. The authors argue that this analysis could be complemented with other information, that is, the structure of non-knowledge. The main objective of this work is to explore the nature and explanatory potential of this new dimension on consumer behaviour in the agrifood context. The principal hypothesis is that, while they may have similar levels of objective knowledge, there are significant differences between the behaviour of consumers who have a predominant pattern of ignorance (tendency to answer “I don't know”) and those who are in error (tendency to give wrong answers).

The present study draws on data derived from five case studies examining consumer knowledge about agrifood products (olive oils, Iberian ham and orange juice) and certain aspects of consumer behaviour. A sample of 4,112 participants was classified into two non-knowledge profiles: wrong, if most items answered incorrectly in a questionnaire were wrong; or ignorant, if most items answered incorrectly were “don't know”.

The results obtained supported the argument that complementing the study of consumer knowledge with an analysis of the structure of non-knowledge is worthwhile, as differences within the structure are associated with different patterns of consumer behaviour.

In the present study, it is proposed that the measurement of knowledge be complemented with an analysis of the consumer's non-knowledge structure (items not answered correctly), given its effects on behaviour, an aspect hitherto unconsidered in the literature. To do so, a new index is proposed.

The market system and a materialistic lifestyle have contributed to some of the environmental and social problems that currently affect the world. However, only a few consumers are willing to express ecological oriented consumption. This study aims to analyse how organic food consumers build a green identity, as well as the new expressions that arise from this identity construction.

A hermeneutical approach was adopted to address the narratives of 31 frequent consumers of organic products motivated by environmental issues. The narratives were collected through the interview method, which was further complemented by participant observation.

The following five phases of identity formation were identified: consciousness, gathering, negotiation, stabilisation and sharing. By looking at the different identity stages, it becomes visible how organic consumption and pro-environmental behaviours act as transformative practices, promoting ecological activism and fortifying a green identity.

This study extends the “processual theory of identity” by analysing how organic products help shape consumer practices and their lifestyle. Moreover, a contribution is provided on how we can build an ecological citizenship by reducing consumption and also by adopting alternative practices of consumption.

Public perception of health benefits derived from organic foods is often misaligned with scientific evidence. This study aims to examine the factors affecting public perception of scientific information about organic foods.

The authors conducted multinominal and multiple linear regression analyses to examine associations between public perception of scientific information about organic foods and 19 factors using data from a descriptive survey (N = 763).

Perceived benefits of organic foods, trust in scientists, communicator credibility, preexisting beliefs and events related to science (e.g. COVID-19) were significant predictors of public perception of scientific information about organic foods.

Cognitive dissonance and recreancy theoretical frameworks help describe relationships between beliefs, science, trust and risk. These theories intersect when purchasing credence goods (i.e. organic foods) whose qualities cannot be observed during or after purchase. Hence, public trust of scientific information about perceived health benefits of organic foods may conflict with strongly held beliefs that contradict scientific findings.

Scientists can more effectively share research findings after trust is established through the listening, asking and sharing values process. Therefore, by following the path of listening, asking and sharing the endogenous/exogenous factors in this study, scientists and the public can have meaningful conversations about perceived health benefits and nutritional values of organically and conventionally grown foods.

Current research on perception factors about organic foods often examined consumers' perceptions and purchase intentions but rarely considered perceptions of scientific information about organic foods. This study examined relationships between public perception of scientific information about organic foods and endogenous/exogenous factors.