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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.

In this chapter a structural equation model is presented to quantify the effect of four independent variables: Information sharing, Collaboration with suppliers, Employee performance, and Supply chain performance, which are related through six hypotheses and validated with the partial least square technique in the WarpPls 6.0 software. The model is validated with data from 254 surveys obtained in the manufacturing industry in Mexico. Similarly, a sensitivity analysis is reported for each of the proposed hypotheses. The results indicate that the most relevant variable in the supply chain performance is the appropriate employee performance.

Multiple studies have analyzed the importance of preventive maintenance. Similarly, they have developed and/or evaluated various spare part inventory management policies that help companies reduce the duration of production disruptions resulting from sudden mechanical failures. All of these studies assess the impact of mechanical failures on local aspects, such as idle times or management policies. However, they do not holistically evaluate how machine failures affect key performance indicators. To address this gap, we proposed a System Dynamics (SD) model to systemically analyze the impact of machine part failures on order shipping, a key performance indicator. Similarly, we assessed the impact of machine part failures on the levels of the company&rsquo, s finished goods inventory. The research was conducted in a glass bottle manufacturing company. To increase order shipping as a performance indicator, we identified the key variables of the production process and conducted a sensitivity analysis of the variables. Our results indicate that it is possible to reach the company&rsquo, s 98&ndash, 100% complete delivery policy.

Current competitive, complex, and uncertain markets drive companies toward increasing active collaboration among human resources involved in a supply chain. Increasing employee participation and supply chain collaboration results in increasing the performance, competitiveness, and, consequently, economic success for companies. In this article, a structural equation model is proposed with three independent latent variables (role of managers, learning environment, employee competencies) and one dependent latent variable (supply chain performance), where six hypotheses to measure their relationships are proposed. The model is validated with data obtained from 284 valid responses to a survey applied to supply chain managers and engineers in the Mexican manufacturing sector. The findings revealed a positive relationship among latent variables, and in terms of magnitude, the role of managers reported the largest effect on the supply chain learning environment.

This paper reports a second-order structural equation model composed of four variables: the green attributes before and after an industrial production process, the operating benefits, the commercial benefits, and the economic benefits. The variables are related by means of five hypotheses and are validated statistically with information obtained from 559 responses to a questionnaire applied to the Mexican maquila industry. The model is evaluated using the technique of partial least squares and the results obtained indicate that the green attributes before and after the production process have a direct and positive effect on the obtained benefits, mostly on the operational ones. It is concluded that companies that are focused on increasing their greenness level must monitor and evaluate the existence of green attributes in their production process to guarantee benefits and make fast decisions if required due to deviations.

The supplier selection process is one of the daily activities of purchasing departments in the maquiladora industries, but traditionally the attributes analyzed are those that can be quantified, ignoring others because its impact on the production process or on the company's revenues is unknown. This article presents a structural equation model in which three latent variables associated with administrative attributes are integrated, the benefits obtained along production process and marketing, where three hypotheses which relate them are exposed. The information is derived from a survey of 253 managers who work in maquiladoras in Mexico, thus, a descriptive analysis of the sample and the items are obtained. The hypotheses were validated according to a structural equation model and the results indicate that there is a direct and positive effect between the variables analyzed, but the most interesting due to its size, is between the profits made by the production process and the marketing benefits.

Nowadays, green supplier selection (GSS) is one of the most important activities for companies. Therefore, this research aims to demonstrate the relationship that exists between GSS and the marketing benefits of companies. The chapter proposes a structural equation model that integrates three latent variables. The two independent latent variables concern preproduction green attributes and process green attributes, and they are associated with a dependent latent variable: marketing indexes. Thus, three hypotheses are proposed to relate these latent variables. To validate such hypotheses, a survey is administered to 253 middle and senior managers from the manufacturing industry of Ciudad Juárez. Similarly, a descriptive analysis of the sample and the items is carried out. Results show direct and positive effects among the analyzed variables. However, the highest impact is caused by preproduction green attributes over production process green attributes.

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 aim of this study is to quantify the impact of information and communication technologies (ICT) and its technological updates on the success of the green supply chain (GSC) implementation, as well as the benefits this affords. This research is applied to the Mexican maquiladora export industry. A model of structural equations is presented to know the importance of the integration of ICT, combined with the implementation of GSC and the generation of benefits with the use of ICT. The results indicate that there is a direct, positive effect (PE) and significant among the four latent variables (LTV) analyzed but the most noteworthy is the indirect effect that the variable updating the ICT has on the benefits of GSC, through the variable mediators&rsquo, implementation of a GSC, since the direct effect of updating the ICT on the benefits of the implementation of GSC does not become significant. Whereby, it is recommended that the industry integrates and updates its ICT since, using the integrated and updated ICT and the implementation of a GSC, a series of economic, productive and environmental benefits will be created.

The process of selection of a supplier plays a fundamental role in the supply chain. With the emergence of the so-called green attributes this process has become more complicated. Besides, it is unknown if the attributes have an impact on the performance of the company. This chapter presents a structural equation model using four latent variables: green policy attributes, green attributes preproduction, green attributes in production processes, and green attributes postproduction to determine the dependence among them. The relationships define six hypotheses. To validate the model, a sample of 253 interviews to managers of firms located in Mexico was taken. To reduce dimensionality the partial least squares (PLS) method was used. The results indicate that there is a direct and positive impact among the variables analyzed. However, the most significant is the relationship between the green policy and the green attributes preproduction.

Supplier selection process is one of the daily activities of purchasing departments in the maquiladora industries, but traditionally the attributes analyzed are those that can be quantified, ignoring others because its impact on the production process or on the company's revenues is unknown. This article presents a structural equation model in which three latent variables associated with administrative attributes are integrated, the benefits obtained along production process and marketing, where three hypotheses which relate them are exposed. The information is derived from a survey of 253 managers who works in maquiladoras in Mexico, thus a descriptive analysis of the sample and the items are obtained. The hypotheses were validated according to a structural equation model and the results indicate that there is a direct and positive effect between the variables analyzed, but the most interesting due to its size, is between the profits made by the production process and the marketing benefits.