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Gamification refers to the use of rules and game design techniques to involve and motivate people to achieve their goals. This work proposes an application development architecture that can generate game applications with gamification techniques. As proof of concept, the authors introduce Zeus, a platform for developing ruled-based serious game applications with gamification techniques. Zeus aims at generating gamified applications that can meet the learning goals set by users. These goals will be reflected through both learning and game attributes that users can personally select. To assess the functionality of the authors tool, they conduct a qualitative evaluation of four rule-based serious game applications developed with Zeus to help students learn about arithmetic. They make use of the Fun Toolkit to perform this evaluation in terms of the delivery of both fun and learning experiences. Their findings are encouraging in the context of learning basic arithmetic operations with Zeus game applications.

This paper presents a structural equation model that relates knowledge coordination with access to information in the process of implementing Six Sigma and their impact on the quality and economic benefits obtained. The model integrates four latent variables (knowledge coordination and access to information as independent variables; quality benefits and economic benefits as dependent variables), that are intertwined by five hypotheses validated statistically through the partial least squares technique using data from 301 responses to a survey applied in the maquiladora industry. Findings suggest that to obtain benefits associated with product quality, information and knowledge acquired from Six Sigma, projects must be carefully saved, managed, and analysed with appropriate statistical techniques applied by green and black belts. However, to obtain economic benefits, the information and knowledge must be transformed into benefits associated with quality such as reduction in delivery time, reduction of customer complains and compliance with standards demanded by the customer.

This paper reports a structural equation model to relate three critical success factors for total quality management (TQM) (i.e. managerial commitment, role of quality department, and quality policies) with customer satisfaction benefits through six hypotheses, which are statistically tested with information from 398 responses to a survey applied to Mexican manufacturing industry and using partial least squares technique integrated in WarpPLS v.6 software. The paper also reports a sensitivity analysis based on conditional probabilities for analyze low and high scenarios. Findings indicate that managerial commitment is the most important variable to ensure TQM, yet it depends on the role of the quality department for deploy quality policies and guarantee customer satisfaction. Similarly, sensibility analysis demonstrate that high levels of managerial commitment always guarantee a high performance in quality departments and good quality policies, thereby contributing to customer satisfaction. From this perspective, there are statistical evidence to declare that managers and operators are the main facilitators of TQM success.

New environmental tendencies have been incorporated into supply chains, and suppliers are playing an important role. However, the main problem when selecting a green supplier is determining the attributes that contribute to a green supply chain. Moreover, a lot of companies ignore the benefits gained from green suppliers on economic performance and marketing. Therefore, this chapter reports a structural equation model with three latent variables (Green attributes of suppliers, Marketing benefits, and Manufacturing processes benefits) and three hypotheses are proposed with relationship among them. The model is validated with information from 253 questionnaires administered to Mexican maquiladoras and evaluated using partial least squares. Findings demonstrate that maquiladoras that consider Green attributes in supplier selection process are gaining marketing and economic benefits, contributing to a green supply chain, and improving the corporate image as socially responsible organizations.

The purpose of this chapter is to present the relationship between the external service provider named Third Party Logistics 3PL and the performance of the logistics process in Mexican manufacturing companies, in order to ascertain the contribution of the aspects considered, allowing companies' suggested improvement actions. Through a field research in Ciudad Juarez and making use of an instrument about 3PL, authors considered four variables: transport, transport management, information technologies, and warehouse. To find the causal model with the relationships between the variables, authors used structural equations modelling. That also identified the relevant aspects in 3PL providers companies' manufacturing and collaboration activities realized in the practice. The results indicate that mainly the information technologies and the transport management have a greater influence on the performance of the logistics process in this type of company.

This chapter presents a literature review about the vendor-managed inventory as well as the methods which improve management, to discover, describe, and analyze methodologies that have been used to support the process of the VMI integration and coordination in the supply chain. Authors focus generally on the advantages that are offered by the VMI to achieve cooperation in a vendor-customer relationship. Results reveal that there is a diversity in the methodologies that were implemented, which perhaps relies on the game theory as a recent methodology that was included to achieve long-term relationships between vendor and customer, because currently supply chains are operating in dynamic environments that require greater efforts of integration among all participants or members.

This chapter reports a structural equation model which relate four latent variables associated with employee performance, knowledge transfer, supply chain complexity and flexibility, which incorporate 17 observed variables. The latent variables are related through 6 hypotheses that are tested with data gather from 269 responses to a questionnaire applied to the Mexican maquiladora industry in Mexico. The model is executed using the partial least squares technique to analyze the direct, indirect, and total effects. In the same way, the probabilities of occurrence are obtained in an independent manner, jointly and conditionally for the latent variables analyzed at their high and low levels for each of the hypotheses. Findings indicate that the external knowledge transfer is crucial within the supply chains, since it explains 44.6% of its complexity, 19.5% of the employees’ performance, as well as 10.6% of the supply chain flexibility.

Time series emerge in various applications such as financial data and production data, however, most of the generated data exhibit nonlinear inter-dependency between samples and noise, making necessary the development of methods capable of handling such nonlinearities and other abnormalities. In this paper we present an architecture for prediction of time series embedded in noise. The proposed architecture combines a convolutional and long short term memory (LSTM) layers into a structure similar to an analysis filterbank of two channels. The first element of each channel is a convolutional layer followed by a LSTM, which is able to find temporal dependencies of the signal. Finally the channels are summed to obtain a prediction. We found that the frequency response of the filters resemble a complementary filter bank response, with each channel having a maximum at different bands which could suggest that it characterizes the incoming signal in frequency. Comparisons with other methods demonstrate that the proposed method offer much better results in terms of different error measures.

This study addresses the transport of fresh fruit and vegetables from an independent transporter in Ciudad Juarez, Mexico. Even though the main issue relies on the transport itself, an alternate objective function was proposed to maximize profits of the transporter by considering certain constraints. The main objective of this research is to determine the optimal amount of fruit and vegetables that should be purchased to be transported later to the different destinations to generate the maximum profitability that is possible. The problem is tackled by means of classical methods of problem solving. Moreover, the simplex method employed enables to identify the constraints and determine the optimal solution to the problem that satisfies transport requirements and generates the highest profitability. Finally, results demonstrate that the maximum profit that can be gained is $1,840.00 Mexican pesos during a single trip, satisfying demand of three different businesses.

The present research proposes a structural equation model to integrate four latent variables: managerial commitment, preventive maintenance, total productive maintenance, and productivity benefits. In addition, these variables are related through six research hypotheses that are validated using collected data from 368 surveys administered in the Mexican manufacturing industry. Consequently, the model is evaluated using partial least squares. The results show that managerial commitment is critical to achieve productivity benefits, while preventive maintenance is indispensable to total preventive maintenance. These results may encourage company managers to focus on managerial commitment and implement preventive maintenance programs to guarantee the success of total productive maintenance.

This chapter discusses the role of competitiveness in the manufacturing industry considering particular aspects of this industrial sector throughout the history of Mexico. This conceptualization of competitiveness forces us to discuss the main industrial sectors of the country and their importance to the national economy.

The current paper presents a structural equation model with four variables (Government, Infrastructure, Proximity to market, and supply chain Agility) affecting the Financial performance of a company. Six hypotheses or relationships among variables are proposed, supposing that Government and market Proximity are key elements to achieve a greater Agility in supply chains, considering the regional Infrastructure to determine the impact on Financial performance in manufacturing companies. The model is validated with data from a survey applied to 225 persons in 65 manufacturing companies located in Ciudad Ju&aacute, rez, Chihuahua, Mexico. The model is evaluated using partial least squares, and the findings indicate that there is a direct and positive effect from the Government on regional Infrastructure with a rate of 0.436. When the Government supports the availability of land, energy resources, transportation, telecommunications, mobile telephones, and other services, a positive change is achieved in the Infrastructure and supply chain Agility. Furthermore, the Government also has a direct and positive effect on the market Proximity at a rate of 0.171, consequently, the regional Infrastructure also has an effect on it. Similarly, the market Proximity directly and positively influences the supply chain Agility, as well as a company&rsquo, s Financial performance at a rate of 0.506.

This chapter develops three structural equation models. The first two relate the best manufacturing practices with eight supply chain performance benefits. The third one is a second-order model that associates all the regional impact factors, manufacturing practices, and supply chain benefits studied in previous chapters. Each model proposes its own hypotheses to relate the latent variables. Such hypotheses are statistically tested and validated to confirm their feasibility. Then, the direct, indirect, and total effects are interpreted for each relationship between latent variables. Finally, we propose final conclusions and industrial implications for each model.

This paper presents a structural equation model for analyzing the relationship between four latent variables: infrastructure, production processes, transport benefits, and economic benefits within the supply chain for wine from La Rioja, Spain, by incorporating 12 observed variables. The model proposes six hypothesis that were tested using information gathered from 64 surveys completed by managers of several wineries in the region. The WarpPLS v.5® software (Version 5.0, ScriptWarp Systems, Laredo, TX, USA) was used to execute the model and analyze the direct, indirect, and total effects among latent variables. The results show that the control of production processes is a direct source of economic and transport benefits because of its higher explanatory power of those variables. Similarly, infrastructure is a direct source of transport and production benefits, and some of them are given indirectly. In addition, infrastructure does not have a direct effect on economic benefits; however, there were indirect effects given through production process and transport benefits. Infrastructure is a very important variable because of its influence in the final performance, but also because of its high environmental impact. Finally, economic benefits were explained in 43.8%, 19.1% belonging to production process, 21.1% coming from transport benefits, and 3.7% from infrastructure. © 2018 by the authors.

Six Sigma (SS) is a production philosophy focused on human experiences and knowledge, aimed to minimize defects of products and services. The appropriate implementation of SS requires an education process, reliable data analysis, efficient didactic material, statistical techniques and human knowledge to improve communication and operational benefits. In this article, we present a structural equation model integrating those aspects as latent variables and relating them with ten hypotheses. Data for hypothesis validation were gathered among 301 manufacturing companies, and assessed using partial least squares (PLS) to estimate direct, indirect, and total effects. As results, we found that access to reliable information, trusted analysis and knowledgeable management are crucial for SS implementation at the problem definition stage. Likewise, to execute and control SS projects, it is important to be trained in statistical techniques through clear didactic materials. © 2017 by the authors.

This paper proposes the development of an expert system for ergonomic compatibility assessment on the selection of Advanced Manufacturing Technology (AMT). Actual models for AMT assessment neglect Human Factors and Ergonomic (HFE) attributes and present deficiencies such as high time consumption and complexity. This approach proposes a novel axiomatic design methodology under fuzzy environment including two stages: the generation of fuzzy If-Then rules using Mamdani’s fuzzy inference system and the development of the system by mean of experts’ opinions. A numerical example is presented for the selection of three CNC milling machines using the Weighted Ergonomic Incompatibility Content (WEIC). The expert system leads to the selection of the best alternative containing the minimum WEIC, as the one that better satisfies ergonomic requirements. Development and application of the system may help provide an easier, faster, single or group ergonomic assessment on AMT selection by promoting safer and more ergonomic workplaces in manufacturing companies.

Nowadays, Single Minute Exchange of Dies (SMED) has achieved great industrial popularity. However, it remains unclear to what extent and how SMED implementation at its different stages benefits industries. To address this gap, this research proposes a structural equation model to quantitatively measure SMED effects. The model has six hypotheses that link SMED stages and benefits. To statistically validate such hypotheses, a questionnaire was administered to 373 Mexican maquiladoras located in Ciudad Juárez, Chihuahua. Results show that before starting SMED implementation process, companies must be appropriately familiarized with their production process. Mainly, manufacturing companies in Ciudad Juárez need to focus their efforts on the SMED planning stage (Step 1) in order to identify important internal production activities and turn them into external activities. In fact, SMED planning stage has direct and indirect effects on subsequent stages and SMED benefits. © 2016 by the author.