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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.

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.

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.

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.

As previously mentioned, the goal of this book is to assess the effects of manufacturing practices and risk factors on supply chain performance. This chapter introduces a series of structural equation models to assess the relationships between three types of supply chain risk factors—supply risks, demand risks, production process risks—and supply chain performance indices. The models are measured and tested as described in the methodology chapter.

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.

Background In developing countries such as Mexico, the effects of burnout syndrome (BS) are observed in manufacturing industries. However, the relationships among BS, Job Content (JC), and Musculoskeletal Complaints (MC) are scarcely studied within the manufacturing sector, even though senior and middle managers are exposed to highly demanding and mentally exhausting situations. Objectives The objective of this paper is to determine the relationships among the three BS dimensions, MC, and JC among middle and senior managers of the manufacturing industry in Ciudad Juarez, Mexico. Methods The Maslach Burnout Inventory-General Survey (MBI-GS), the Job Content Questionnaire (JCQ), and the Body Map assessment were administered as data collection instruments. The sample included 361 participants from six industries located in Ciudad Juarez, Mexico. Also, we proposed structural equations models (SEM) to establish the relationships among variables. Results The questionnaires and the model showed acceptable reliability and quality indices. Emotional exhaustion was the most relevant latent variable, having significant effects on MC and on professional efficacy, and significantly contributing to increasing levels of cynicism. On the other hand, the variable social support showed a negative direct impact on Job Demands and Emotional Exhaustion. Conclusions Actions to reduce emotional exhaustion at work include providing a positive and suitable work environment through social support. These strategies help prevent MC and improve professional efficacy, life quality at work, and productivity.

Macroergonomics contributes to competitiveness of manufacturing systems; however, it seems that macroergonomic practices are scarcely implemented in Mexican manufacturing companies. The objective of this article is to determine the relationships between two macroergonomic elements, Organizational Culture and Teamwork, and manufacturing systems’ performance (Manufacturing Processes, Customers, and Organizational Performance). As data collection instrument, we administered the Macro-Ergonomic Compatibility Questionnaire (MCQ) to 188 employees of manufacturing companies located in Ciudad Juarez, Chihuahua. Then, a structural equation model (SEM) was constructed to know and measure direct, indirect, and total effects occurring among latent variables. Findings revealed a good model fit and showed that Organizational Culture and Teamwork have the same direct and positive effects on manufacturing systems’ performance. In conclusion, macroergonomic practices of Organizational Culture and Teamwork contribute to improving performance and competitiveness of manufacturing systems.

Empirical research carried out in many contexts has found that social support is an important element to reduce the effects of burnout. In this chapter, we analyze the relationships between social support and the three dimensions of burnout syndrome (BS) (emotional exhaustion, cynicism, and professional efficacy). The research was carried out in six manufacturing companies from Ciudad Juarez, Mexico, and the sample included 361 middle and senior managers from different departments. Two questionnaires were administered in the form of a single survey: The Maslach Burnout Inventory–General Survey and the Job Content Questionnaire (JCQ). The former analyzed the three burnout dimensions, whereas the latter studied social support. Relationships between latent variables were analyzed using the structural equation modeling technique (SEM). Results showed a statistically direct relationship between social support and the three burnout dimensions. On one hand, the effects of social support on emotional exhaustion and cynicism are negative. That is, both dimensions diminish when workers perceive enough support from their supervisors and coworkers. On the other hand, the relationship between social support and professional efficacy is positive, meaning that efficiency at work increases when workers perceive enough support from their work team. As conclusions, manufacturing companies must invest in techniques, such as engagement, empowerment, resilience, and social support, to ensure employee motivation and integration. Such strategies impact the wellbeing of companies by reducing burnout effects.

This paper proposes a structural equation model to assess the effects of some risk factors in the supply chain performance. The model includes demand, suppliers and processes as risk factors of a case study in Ciudad Juarez, Chihuahua, México. The model, assessed following a structural equation modeling methodology (using AMOS 16.0), indicated that the demand (considered as an independent factor) has a direct positive relationship with suppliers, politics, and manufacturing factors. As a consequence the suppliers have an effect on the flexibility factor. The flexibility has a direct positive relationship with the customer service factor. The results also indicate that the infrastructure factor does not have any relationship with the others assessed factors. The study has important implications for researches and practitioners in the manufacturing sector. It allows evaluating risk activities that have negative effects on the performance of supply chain in manufacturing exports companies in México.

Mexican maquiladoras (Mexican export processing plants) are focused on exportation activities, and have several processes derived from policies related to procurement and inventory that are established by each company. This paper analyzed 17 activities related to supply chain (SC) policies and grouped them into four independent latent variables: (1) traditional logistics, (2) international logistics, (3) supply, and (4) inventories. Moreover, the impact of these policies was analyzed on ten benefits and was eventually grouped into three dependent latent variables. In order to analyze the relationship among these latent variables and to generate a measurement model, a survey was conducted in 63 exportation Mexican maquiladoras located in Ciudad Juarez, Chihuahua. Twelve hypotheses about the relationships among latent variables were then generated in order to determine the causal relationships. Finally, the hypotheses were integrated in a structural equation model (SEM) and tested using partial least squares technique that is integrated in WarpPLS® software. The obtained results indicated that traditional logistics policies have a direct impact on the inventory, international logistics, and supply variables. This impact allows for greater efficiency in the supply chain, better economic performance, and more satisfied customers.

Este trabajo presenta un análisis de los efectos que tienen la infraestructura regional y los servicios en el desempeño de la cadena de suministro en empresas manufactureras de Ciudad Juárez, Chihuahua, México. Para colectar la información se aplicaron cuestionarios a 120 empresas, y para obtener un modelo de ecuaciones estructurales explicativo de los efectos se utilizó la metodología de mínimos cuadrados parciales usando WarpPLS 3.0. Los resultados obtenidos muestran que cuando existe buen nivel en la infraestructura regional se tienen impactos positivos sobre los servicios logísticos; y éstos a su vez impactan en los costos. Asimismo, la infraestructura regional tiene impactos positivos sobre el tiempo de entrega de los productos. Con relación al nivel de infraestructura (transporte, telecomunicaciones, internet) y de servicios (aéreos, terrestres, financieros, legales) en Ciudad Juárez, los encuestados lo consideran bueno por lo que las entregas de producto han sido completas y a tiempo en los últimos 3 años. In this paper appears an analysis of the effects of regional infrastructure and the services in the supply chains performance in manufacturing companies collated in Ciudad Juarez, Chihuahua, Mexico. To collect the information, 120 surveys were applied to companies, and to obtain a causal with structural equation modelling to explain those effects, a methodology of partial least squares was used with WarpPls 3.0®. The results indicate that a good level in the regional infrastructure has a positive impact on logistics services, and as a consequence in the costs. Also, the regional infrastructure has a positive impact on time delivery of products. Regarding the level of infrastructure (transport, telecommunications, and internet) and services (air, land, financial, legal) in Ciudad Juarez, respondents are considering that it is good, so the product deliveries are complete on time in the past 3 years.

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 research relates Burnout Syndrome (BS) with the Body Mass Index (BMI) among middle and senior managers of the Mexican manufacturing industry. Even though BS incidence is high in the Mexican industrial population, few systematic studies have explored BS and its relationship with other health problems, such as obesity. The goal of this research is to determine the relationship between BS and the BMI in employees with normal weight, overweight, and obesity. We present three structural equation models to relate BS and the BMI. The BMI ranges were determined according to the parameters (normal weight, overweight, and obesity) proposed by the World Health Organization (WHO). The sample includes 361 employees that voluntarily answered a 31-item questionnaire. We measure the levels of BS using the Maslach Burnout Inventory–General Survey (MBI-GS) and analyze anthropometric and sociodemographic data from the participants. Then, we determine the relationships between the variables through structural equation models and estimate the direct, indirect, and total effects in the three models, which show acceptable reliability. As main findings, the normal weight model has a larger explanatory power than the overweight and obesity models. The same research hypotheses were tested and the effects of BS on the BMI differ across the three models. Such results are presented by taking into account that obesity and overweight require additional factors, such as genetic factors and personal eating habits, to be better explained.