Search

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.

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.

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.

Mexico has received a lot of foreign investment that has brought in a wide range of novel production philosophies, such as Single Minute Exchange of Dies (SMED). Despite its popularity and reported effectiveness, Mexican companies often quit SMED implementation as they consider it challenging. This usually happens when organizations are not familiarized enough with each one of the SMED stages or do not know how they are interrelated. In this article the interrelations among the different SMED implementation stages by means of a structural equations model are analyzed. Data for constructing the model were gathered from a survey administered to 250 employees from the Mexican maquiladora industry. The survey assessed the importance of 14 activities belonging to the four SMED stages. The descriptive analyses of these stages were conducted and integrated into a structural equations model as latent variables, to find their level of dependency. The model was constructed using WarpPLS 5 software, and direct, indirect, and total effects among variables are analyzed and validated. Results from the model revealed that Stage 1 of SMED implementation, known as the Identification Stage, has both direct and indirect effects on all the other SMED stages, being the most important stage.

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.