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Managers implement several Green Supply Chain Management (GSCM) practices to improve sustainability and economic performance, such as environmental management systems (EMS), eco-design (ED), source reduction (SR) and attending to external environmental management (EEM) requirements; however, the relationship among them requires a deep study. This paper reports the case of the Mexican maquiladora industry, analyzing the main relationships among GSCM practices with environmental impact (EI) and environmental cost savings (ECS). The analysis reports three structural equation models (SEM) developed as simple, second-order, and mediating models. Those relationships are tested using 160 responses to a survey applied to the Mexican maquiladora industry and with partial least squares algorithms (PLS), where conditional probabilities for different scenarios in latent variables are also reported. Findings indicate that EMS has a direct effect on EI (β = 0.442) and ECS (β = 0.227), indicating that EMS reduces EI and cost associated with the production process; however, ED has no direct effect on EI (β = 0.019) and ECS ((β = 0.006), and it can be due to the maquiladora nature as foreign companies focused on manufacturing and not to product design. This research was funded by Mexican National Council for Science and Technology (Consejo Nacional de Ciencia y Tecnología, CONACYT), grant number 858463 and the APC was funded by all authors.

Purpose The purpose of this paper is to measure the relationships between advanced manufacturing technologies (AMTs) categories (stand-alone, intermediated and integrated systems) implementation and design, process and commercial benefits obtained. Design/methodology/approach A survey is designed with benefits gained from AMT implementation as well as its categories, which is applied to the maquiladora industry. A structural equation model with data from 383 responses is used to measure the relationship between AMT categories and benefits gained using nine hypotheses that are tested statistically significant using partial least squares. Also, using conditional probabilities, a sensitivity analysis reports how low and high levels from AMT implementation influence on the obtained benefits. Findings Integrated systems are the most important AMT for maquiladoras and have the strongest impact on design, processes and commercial benefits. Research limitations/implications Data obtained support the model, but results may be different in another industrial sector and countries with different labor culture and technological level. Practical implications Managers in maquiladora industry must focus their attention on integrated manufacturing systems, because high implementation levels guarantee the biggest probability to gain benefits in design, production process and commercial. Originality/value The relationship between AMT and their benefits has not been measured in depth, and this paper contributes to understand that problem. In addition, this paper is the first to report a sensitivity analysis that enables managers to acknowledge the probability of obtaining certain benefits.

Nowadays, companies are requiring a fast response to market, and supply chain must be adapted. This paper presents a structural equation model (SEM) integrating advanced manufacturing technology, pull system, responsiveness to market as independent latent variables, and responsive supply chain strategy as dependent latent variable. Those variables are related using six hypotheses. The SEM is aimed to measure the effect among latent variables and identify the most important activities that have the greatest effect. The SEM is statistically validated using information from 254 responses to a questionnaire applied in the manufacturing industry, and the partial least squares (PLS) technique is used. Findings indicate that advanced manufacturing technologies indirectly support companies to be able to respond to changes in demand and allow them to offer a rapid response in the changing market through the pull system implementation.

This chapter reports a model of structural equations that integrates three independent variables: Total productive maintenance, just in time and Overall equipment efficiency and the relationship they have with Social sustainability as a dependent variable. The four variables are related through six hypotheses that are validated with information gathered from 239 questionnaires answered by executives laboring at Mexican maquiladora industry. The partial least squares technique is used to statistically validate the relationships among variables. Findings indicate that Total predictive maintenance has a strong impact on Overall equipment efficiency and Just in time, and the variables that most influence Social sustainability are Total predictive maintenance and Just in time. It is concluded that Social sustainability can be obtained through proper use and maintenance of the machines and with timely fulfillment of production orders.

This paper presents a second-order structural equation model that analyzes three lean manufacturing tools associated with material flow, such as 5S, SMED, and continuous flow related to economic sustainability. The variables relate to each other through six hypotheses, tested with 169 responses to a questionnaire applied to the Mexican maquiladora industry, using the partial least squares technique and 95% confidence to estimate direct, the sum of indirect, and total effects. In addition, an analysis with conditional probabilities appears to determine how low and high implementation levels in independent variables affect the dependent variables’ occurrence. Findings indicate that 5S is a lean manufacturing tool with the most increased direct effects on SMED and continuous flow. Additionally, values indicate that SMED is essential to maintain continuous flow in production lines and is vital for economic sustainability due to the time reduction in setup.

This paper reports a structural equation model (SEM) to quantify the relationship between Lean Manufacturing (LM) tools associated with machinery and sustainability. The LM tools are inde-pendent variables and include Total Productive Maintenance (TPM), Jidoka, and overall equipment effectiveness (OEE), whereas dependent sustainability variables comprise environmental, social, and economic sustainability. The SEM proposes ten hypotheses, tested statistically using information from 239 responses to a questionnaire applied to the Mexican maquiladora industry and the Partial Least Squares (PLS) technique for quantifying relationships among variables. Additionally, we discuss conditional probabilities to explain how low and high levels of TPM, Jidoka, and OEE impact sustainability. Findings reveal that TPM, Jidoka, and OEE directly impact social, environmental, and economic sustainability, thus indicating that safe workplaces improve employee commitment, safety, delivery time, and morale. This research was funded by Consejo Nacional de Ciencia y Tecnología (CONACyT) from Mexico, grant number 858463.

This paper presents the effects between Logistics Network and Value-Added activities 3PL environments and its effect on the Financial and Strategic Performance of Mexican Maquiladoras companies. The significant increase in outsourcing transportation services in freight transport at the border Mexico-United States has inspired this research. The paper presents four hypotheses, tested with data from 158 responses to a questionnaire applied to engineers from the manufacturing industry in Ciudad Juarez (Mexico). The hypotheses were tested statistically using the partial least squares technique. Results indicate that a good design of a Logistics Network has a positive effect on Strategic Performance through transport logistics planning to reduce distribution times and costs. Additionally, the Value-Added services offered by a 3PL positively affect Strategic Performance through labeling-marking, packaging, and reassembling of products. Also, the Strategic Performance has a positive effect on Financial Performance through flexibility and risk minimization of 3PL provider, and this is the enormous effect that arguing theoretically and demonstrating empirically that the outsourcing of 3PL incremented the economic benefits to the quantity of 76.20% between Financial Performance and provides a reference to make decisions according to strategies to incorporate 3PL in such maquiladora industries. Keywords: 3PL, strategic performance, financial performance, structural equations

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.

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.

This chapter presents some data related to the evolution of total productive maintenance in recent decades, specifically from 1994. As a matter of fact, the data is organized according to the type of publication, the published, number as well as the TPM use trend, information is presented on the number of published articles by each journal, the authors that publish information about TPM, and the industrial sectors that implement this tool. In addition, the data was obtained from a literature review in different databases, where keywords were used such as total productive maintenance (TPM). Also, the results show that in 2015, it was the year where more papers were published about TPM, the most common type of publication is research articles with 714, the journal with the most reported publications is International Journal of Production Economics, the sector that uses it more is the construction of industrial buildings, and the editorial that has published the most is Taylor & Francis LTD. Similarly, a series of case studies are included that demonstrate the success of the TPM implementation, both in the manufacturing industry and in-service companies.