Aida Huerta Barrientos

By Aida Huerta Barrientos and Idalia Flores de la Mota

The aim of this chapter is to characterize sustainable supply chain management as a complex adaptive system (CAS) and develop an evolutionary game theory-based model to understand how cooperation emerges from interactions among companies to adopt sustainable management practices. We consider two interacting populations 1 and 2, each one with heterogeneous companies belonging to the same supply chain. One population is expected to behave cooperatively in adopting sustainable management practices while the other is expected to behave uncooperatively. The mathematical model we propose is game-dynamical replicator equations for multiple populations in the prisoner´s dilemma (PD) game and we implement it using NetLogo software. The proportion of cooperative companies in each population that adopt sustainable management practices evolves positively over time as companies only imitate the adoption of sustainable management practices in their own population and in the populations of their partners when the benefit obtained by cooperating is maximum. The spatial patterns observed help us to clarify the preconditions for the emergence of cooperation among companies in managing material, information and capital flows in a sustainable way. Finally, our simulation results show that the sustainable management of supply chains needs to be studied as CASs, in order to take into account the social side of sustainability.

Part of the book: Sustainable Supply Chain Management

By Aida Huerta Barrientos and Yazmin Dillarza Andrade

Socio-environmental innovation is a process of social change that implies both the participation of agents on social and environmental initiatives and the generation and diffusion of relevant information, which lead social transformations for collective benefit. During the diffusion of socio-environmental innovations through a communication network, the information is created and shared among participants until mutual understanding is reached. In the case of National Network for Sustainable Rural Development (RENDRUS) network, getting innovations adopted is very difficult by people in rural communities due to the lack of effective communication channel. This study aims to develop a novel agent-based simulation model of socio-environmental innovation diffusion in the RENDRUS network based on complex adaptive systems approach. First, the conceptual model of socio-environmental innovation diffusion in the RENDRUS network based on complexity approach is developed. Then, an agent-based simulation model is implemented using Netlogo software, followed by the simulation model analysis and the design of plausible simulation scenarios. The simulation results illustrate how S-curve emerges from the interrelationships between agents considering endogenous and social cohesion effects. The conclusions argue that more social cohesion and popularity of socio-environmental innovations between small rural producers and their organizations, governmental institutions, academic institutions and the knowledge society corresponds to less time to adopt socio-environmental innovations.

Part of the book: Computer Simulation

By Aida Huerta Barrientos

Mexico has been characterized by its great linguistic diversity concentrating 364 native linguistic variants from 11 native linguistic families. Unfortunately, the risk of disappearing of Mexican indigenous languages represents a problem for Mexican culture since they are precisely the medium through which cultural knowledge is transmitted. The risk of disappearing is reflected on a small number of native speakers and their geographical dispersion, the prevalence of adult speakers, and the tendency to abandon transmission strategies to youngest generations. The aim of this chapter is to analyze the impact of idiolect mutations on the evolutionary dynamics of the linguistic group Mixe in Camotlán, San Sebastian, Puxmetacán, Mazatlan, and Coatlán communities. First, we develop a conceptual model of the linguistic group Mixe as complex adaptive system, followed by the implementation of an agent-based simulation model in NetLogo, and finally, we analyze the evolutionary dynamics of the Mixe language, depending on the mutation rate of the idiolects. From the simulation analysis, we observe that when the mutation rate in idiolects is equal to zero, the Mixe language becomes homogenous. On the contrary, when the rate of mutations is equal to 100, a large number of language variants are generated and the risk of disappearing increases for Mixe language.

Part of the book: Sociolinguistics

By Aida Huerta‐Barrientos

In Mexico, traditional extension models have been linear, also they lack orientation towards the demands of the producers and the demands of the markets, the approach has been in general paternalistic and the attention is by individual producers. These extension models have not been sufficiently effective in promoting and adopting socio‐environmental innovations to create value along the supply chain. The principal purpose of this chapter is to understand, on the one hand, the elements of a novel integral extension model, and on the other hand, its key role in socio‐environmental innovation for contributing to achieve sustainable development in rural areas in Mexico. The integral extension model proposes the participation of extension workers as facilitators of the learning process to orient the change of attitudes and behaviors of local/regional actors, carrying out the socio‐technical‐environmental support to producers throughout the value chain perspective. Also, traditional and science‐based knowledge need to interact synergistically ensuring that further value is added to traditional knowledge of local producers. In conclusion, integral extension system plays a crucial role in the implementation of strategies for sustainable rural development in Mexico because it promotes models of interactions among local/regional actors consistently with future as well as present needs.

Part of the book: Management of Cities and Regions

By Aida Huerta-Barrientos

Large cities are usually wealthier, denser in terms of population, more expensive, more congested but also more productive culturally and technologically. Mexico City is one of the most dynamic cities of the global economy but also presents the highest crime and congestion levels on the road network. The socio-metabolic approach interprets cities as a socio-metabolic system that interacts with systems in the natural environment. Although considerable progress has been made in studying cities as complex adaptive systems using such approach, many important issues such as social and innovation dimensions remain unexplored, mainly in Mexico City context. The principal purpose of this study is to analyze the metabolic scaling of socio-cultural and technological aspects in the context of Mexico City in order to predict the energy necessary to maintain the city socially connected and to estimate the impact of such social connections on the socio-economic-environmental indicators. We take into account the total population, the cultural infrastructure, the social cohesion, the traffic congestion level, the cost of fuel car, the minimum income, and the number of patents in the analysis as the agglomeration effects in Mexico City. We consider this study can support the design of public policies using the metabolic approach.

Part of the book: Urban Agglomeration

By Aida Huerta Barrientos, Alma Elia Vera Morales and Tania Vázquez González

The rural poverty in Mexico is mainly due to the lack of access to basic services, resources, technology, and scientific knowledge. Despite the Mexican government´s efforts to contribute on improving income levels and employment in rural communities, the challenge that faces the communities to achieve sustainable development is very significant. The principal purpose of the study is to analyze the metabolic scaling of cultural, environmental, and economic aspects in the context of Mexican rural communities in order to predict the energy necessary to maintain them connected and to estimate their impact on the improvement of socio-economic indicators. First, we used the socio-metabolic approach to the study of social complex systems in rural context. The social metabolism approach aims at the study of the material and energy exchange relationships between societies and their natural environment. Then, we analyzed the metabolic scaling of cultural, environmental, and economic aspects in the context of Mexican rural communities. Finally, the energy necessary to maintain the community connected and its impact on the socio-economic indicators was evaluated. We consider that results from this study can support the design of public policies focused on the improving the living conditions of Mexican rural communities.

Part of the book: Culture and Identity

By Aida Huerta Barrientos and Alejandro Nila Luevano

Multi-agent systems (MASs) are defined as a group of interacting entities or agents sharing a common environment that changes over time, with capabilities of perception and action, and the mechanisms for their coordination provide a modern perspective on systems that traditionally were regarded as centralized. The main characteristics of agents are learning and adaptation. In the last few years, MASs have received tremendous attention from scholars in different fields. However, there are still challenges faced by MASs and their integration with machine learning (ML) methods. The primary goal of the study is to provide a broad review of the current developments in the field of MASs combined with ML methods. First, we present features of MASs considering the ML perspective. Second, we provide a classification of applications of MASs combined with ML methods. Third, we present a density map of applications in E-learning, manufacturing, and commerce. We expect this study to serve as a comprehensive resource for researchers and practitioners in the area.

Part of the book: Multi-Agent Technologies and Machine Learning

By David Felipe Mares Silva and Aida Huerta Barrientos

Chatbots, defined as artificial intelligence program able to simulate processes of human conversation via auditory or textual methods, are deployed by firms to automate customer service. In recent years, chatbots have received tremendous attention from scholars in numerous fields including e-health, e-learning, and e-commerce over many sectors. However, the technology developments and applications specifically in the primary healthcare domain are still insufficiently explored. The principal purpose of the study is to provide a broad review of the current technology developments and applications in primary healthcare domain and future directions in the research. First, we describe features of chatbots considering the healthcare domain. Next, we provide a classification of technology developments and applications in primary healthcare with a focus on recent advances. Then, we present a density map of applications in the primary healthcare domain. Furthermore, we introduce future directions in the core research technology. We expect this study to serve as a comprehensive resource for researchers in healthcare domain.

Part of the book: Chatbots