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The purpose of this paper is to propose an economic production quantity (EPQ) inventory model considering imperfect items and probabilistic demand for a two-echelon supply chain. The production process is imperfect and the imperfect quality items are removed from the lot size. The demand rate of the inventory system is random and follows an exponential probability density function and the demand of the retailers is depending on the initiatives of the sales team.

Two approaches are examined. In the non-collaborative approach, any member of the supply chain can be the leader and takes decisions to optimize the profits, and in the collaborative system, all members make joint decisions about the production, supply, sales and inventory to optimize the profits of the supply chain members. The calculus approach is applied to find the maximum profit related to the members of the supply chain.

A numerical example is presented to illustrate the performance of the EPQ model. The results show that collaborative approach generates greater profits to the supply chain and the market’s demand represents the variable behavior and uncertainty that is generated in the replenishment of a supply chain.

The new and major contributions of this research are: the inventory model considers demand for products is random variable which follows an exponential probability distribution function and it also depends on the initiatives of sales teams, the imperfect production system generates defective items, different cycle time are considered in manufacturer and retailers and collaborative and non-collaborative approaches are also studied.

The central motivation for this study was to examine alternatives against the apartment area reduction as a safe way to reduce construction costs, adopted by many construction companies. From the building economic compactness index concept, it was studied the cost and environmental impacts (material consumption, embodied energy – EE and CO₂ emission).

The research strategy takes advantage of a case study aiming to investigate the relation between design characteristics related to area (m²) and building economic compactness index (%) with cost (Research Stage 1) and with environmental impacts: (Research Stage 2). The study involved real data from social housing projects, chosen in terms in terms of very similar features like size, area and constructive method (constants), however, with dissimilar compactness (variable).

The lack of direct relation between area and cost signs the importance of including the cost of vertical plans considered in the economic compactness building. The higher the economic compactness index, the lower the cost, the lower the amount of material, EE and CO₂ emission parameters. However, due to the wide range of EE and CO₂ values available, the reduction in the amount of materials achieved by increasing building economic compactness index may not be reflected in EE and CO₂ gains.

As the limitation of this study, it must be taken into account a limited number of case buildings and the fact that the analysis is dependent on the reliability and accuracy of the data provided by constructors and the available information of EE and CO₂ emission. As well discussed in the literature, the consistent database is a great challenge for the construction sector.

There might be alternatives to higher areas with relatively low-cost increments since results from buildings with the same area present different cost estimative and suggest a strong relationship with the economic compactness index. The large variation of EE and CO₂ emission data indicates that reductions obtained by compactness increase may be impaired if the construction materials are produced with high levels of EE and CO₂ emission. Thus, there must be an integrated effort on the part of designers (design and material specification) and manufacturers (material production), since isolated solutions may not be enough.

The purpose of this paper is to investigate the relations in the Marketing/Operations interface through the analysis of data of the operational reality of a Brazilian company with a low technological intensity. The study aims to quantify and determine the impacts of marketing decisions on delivery performance and on flexibility of the operations area.

A longitudinal case study was conducted and the variables used in the model were derived from established theories and were evaluated with artificial neural networks. The case of a food manufacturing company was selected to reflect the relations in the marketing/operations interface of a low technological intensity enterprise.

The results show that the decisions on Place/Channel, Price and Product dimensions of marketing exert a significant impact on flexibility and delivery performance of the operation area.

The findings of the case study cannot be generalised and the outcomes are specific to just one firm. However, the approach lends itself to replication, particularly within low technological intensity companies.

Prior studies have focussed on coordination among functional areas as marketing and operations at higher levels of abstraction. The study contemplate empirical propositions through the data analysis of a company with a low technological intensity that can be used to improve managers' decisions and alignment in the Marketing/Operation Interface.

The interest paid on own capital can benefit companies in the Brazilian capital market as it can be considered a business expense and is, therefore, deductible as a corporate tax. The purpose of this paper is to assess the impact of interest on equity (IOE) on capital structure decisions.

The initial sample consisted of 524 publicly traded companies from different industries in the Brazilian capital market that were listed on Bovespa. Companies in the finance, insurance and funds industries were excluded from the sample due to the unique features of these financial intermediaries. Some companies in the initial sample were excluded due to a lack of published data, inactivity during the sample period, etc. Thus, the paper excluded those companies that did not have valid observations or failed to publish them. The final sample included 370 companies and covered the nine-year period from 1998 through 2006.

To this end, the authors identified the main determinants of capital structure and analyzed, through panel data, the relationship of IOE in addition to other determinants of capital structure, such as size, profitability, investment opportunities, risk, sales growth, real interest rate and real exchange rate, in corporate debt. The novel contribution of this study is the inclusion and analysis of the IOE in studies on the determination of capital structure of Brazilian companies. A new capital structure scenario was created when Law No. 9.249/95 required changes in legislation, ceasing the restatement of balance sheets and allowing companies to compensate their stockholders through IOE. Before this change, companies could only benefit from the tax benefits of debt, using debt capital. Now, they can also benefit from the use of equity because, by requiting equity through the IOE, deductions of income tax and social contributions on net income are allowed by tax law because the IOE may be considered a financial expense.

: The authors were not able to find any other publication of a similar study in a review of the extant empirical literature.

The purpose of this paper is to analyze the perception of the cold chicken meat value in its supply chain and how to manage the influence of quality demands in this supply chain. It is based on the views that retails and restaurants have about the main quality aspects required to meet their end customers.

This paper surveyed 135 respondents from restaurants, butcheries, supermarkets, and convenience stores located in the Southern Brazilian metropolitan area. Principal component analysis followed by quality function deployment was performed to analyze the data.

The principal component analysis results in seven factors: product quality and flexibility of delivery; supply flexibility; responsiveness to market changes and product assortment; measurements of the inventory and competitiveness; product specificity; product availability and specificity cost; and delivery frequency. The comparative study on the steps of the process between restaurants and retailers shows that distribution, cutting and packaging are the key process steps in this chain.

The results show what process steps must be prioritized to comply with the customers’ quality requirements. Since the most important process steps are different for different customers, companies may elect what steps require more attention to satisfy the most profitable customer types.

Several studies are found in the literature that present a theoretical discussion on the quality demands of perishable products. The management of factors related to the process steps can help members of the supply chain in their decision-making processes. The contribution of this research is to identify, by an applied study, how the demanded quality aspects should be considered by the poultry industry to satisfy customers in different market segments.

The purpose of this study is to suggest the joint use of computer-aided design (CAD) and additive manufacturing (AM) technology for the fabrication of custom-made moulds, designed for the manufacture of polymethyl methacrylate (PMMA) implants for cranio-maxillofacial reconstruction to reduce their fabrication time. Even though tailor-made skull prostheses with a high technological level and state-of-the-art materials are available in the market, they are not always accessible to the general population in developing countries.

Computed tomography data were handled to create a three-dimensional (3D) model of the injury of the patient, by reconstructing Digital Imaging and Communications in Medicine (DICOM) images into an Standard Tessellation Language (STL) file that was further used to design the corresponding implant using CAD software. Accordingly, a two-piece core and cavity moulds that replicated the implant geometry was also CAD designed. The 3D-CAD data were sent to an AM machine (fused deposition modelling) and the moulds were fabricated using polycarbonate as thermoplastic material. A reacting mixture to produce PMMA was poured directly into the fabricated moulds, and left to polymerise until cure. Finally, a clear bubble-free case of study PMMA implant was obtained.

The fabrication of CAD-designed moulds with AM, replacing the production of the injury model, resulted in the reduction of the lead-time in the manufacturing of PMMA around 45 per cent. Additionally, the implant showed better fit than the one produced by conventional process. The use of AM moulds for the fabrication of PMMA implants has demonstrated the reduction in lead-time, which potentially can reduce the waiting time for patients.

Currently, the demand of cranio-maxillofacial implants at only the Hospital General de México “Dr Eduardo Liceaga” (HGM) is 4,000 implants per year, and the average waiting time for each patient is between 5 and 10 weeks, including third-party services’ delays and the time needed to obtain the economical resources by the patient. Public hospitals in Mexico lack manufacturing facilities, so patients have to make use of laboratories abroad and most of the population have no access to them. The implementation of this suggested procedure in public hospitals may improve the accuracy of the implant, increase the number of patients attended per year (up to 83 per cent) and the reduction in waiting time can also reduce mortality and infection rates.

The authors of this paper suggest the joint use of CAD and AM technologies to significantly reduce the production time of PMMA implants by producing moulds rather than the injury model, maintaining the general terms and known steps of the process already established for PMMA implants.

Drum-Buffer-Rope (DBR) is a method to adjust production flows, synchronize the release of materials and enable a process of focused improvement in production systems. Literature on DBR applications in engineer-to-order (ETO) production systems, where customers participate in product design decisions and, consequently, in the way production is planned and executed, is rare. However, the interest in improving production management in ETO systems has received attention from the scientific and business communities. The goal of this research was to evaluate the implementation of DBR in an ETO productive system, critically analyzing the necessary adaptations for its use.

This research was conducted through a case study in a company that manufactures electronic equipment, known as avionics, in the aerospace sector.

In this context, the contribution of this study consists of evaluation of the implementation of DBR in an ETO productive system, describing the implementation and the necessary adaptations of the DBR to the ETO productive system explored, comparing it with the DBR theoretical proposals and Simplified Drum-Buffer-Rope (S-DBR) methods.

The study contributes to knowledge by expanding the field of the DBR application to make it more precise, and by applying the theory of constraints, in a general manner, to this type of productive environment.

The purpose of this paper is to examine how corporate social responsibility (CSR) initiatives add value to Brazilian companies and how these companies perceive the impact of CSR initiatives on their customers, employees, and society.

A multiple case study was conducted on 17 Brazilian companies, from diverse industries, that started their CSR initiatives between 1984 and 2011.

It is possible to identify ten companies with CSR initiatives disconnected from business strategy. In such cases, CSR started as an altruistic contribution to the local community. Actions have been limited to the employees and have demanded resources without perceived value for stakeholders. In seven companies, CSR initiatives are linked to the business strategy. In these cases, CSR initiatives add value to the companies promoting companies’ or brands’ reputation. It is observed to provide better working environment through employees’ motivation and their involvement in CSR initiatives. This value is perceived for the customers, employees, and for the society. However, to reinforce this perception, interested stakeholders should be informed about CSR initiatives and their contribution to the society.

This research attempts to analyze the CSR initiatives of the companies in emerging countries and to understand how CSR could add value to these companies and how this value is perceived. It also aims to understand how these initiatives have been organized and could support the altruistic efforts with effective results to the companies and to the society.

The purpose of this paper is to develop a multi-item economic production quantity (EPQ) strategy under grey environment and space constraint. Since the “demand” cannot be predicted with certainty, it is assumed that data behave under grey environment and compare the proposed inventory model with other studies using crisp or fuzzy environments.

This paper is to optimise the cycle time and total cost of the multi-item EPQ inventory model. For this purpose, the Lagrangian coefficient is used to solve the constrained optimisation problem. The grey relational analysis approach and grey data are applied in developing the EPQ inventory model.

The results are compared with the analysis using crisp and fuzzy data. Sensitivity analysis is done to illustrate the effect of parameter variations on the optimal solution. The results of the study demonstrate that crisp data outperform the other two data in all scales problems in terms of cycle time and cost; grey data perform better in all scales problems than fuzzy data.

The contribution of this research is the use of grey data in developing the EPQ inventory model with space constraint.

The purpose of this study is to evaluate the efficiency of a Brazilian steelmaking company’s reheating process of the hot rolling mill.

The research method is a quantitative modeling. The main research techniques are data envelopment analysis, TOBIT regression and simulation supported by artificial neural networks. The model’s input and output variables consist of the average billet weight, number of billets processed in a batch, gas consumption, thermal efficiency, backlog and production yield within a specific period. The analysis spans 20 months.

The key findings include an average current efficiency of 81%, identification of influential variables (average billet weight, billet count and gas consumption) and simulated analysis. Among the simulated scenarios, the most promising achieved an average efficiency of 95% through increased equipment availability and billet size.

Additional favorable simulated scenarios entail the utilization of higher pre-reheating temperatures for cold billets, representing a large amount of savings in gas consumption and a reduction in CO2 emissions.

This study’s primary innovation lies in providing steelmaking practitioners with a systematic approach to evaluating and enhancing the efficiency of reheating processes.