Product-portfolio management: A framework based on Methods, Organization, and Strategy

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Fishery of the Uçá Crab Ucides Cordatus (Linnaeus, 1763) in a Mangrove Area in Cananéia, State of São Paulo, Brazil: Fishery Performance, Exploitation Patterns and Factors Affecting the Catches

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

A comparative study of production performance and animal health practices in organic and conventional dairy systems

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

INFLUENCE OF THE VENEER-FRAMEWORK INTERFACE ON THE MECHANICAL BEHAVIOR OF CERAMIC VENEERS: A NONLINEAR FINITE ELEMENT ANALYSIS

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Definição de framework para a padronização de processos em um periódico científico com base em revisão da literatura e nos objetivos de desempenho

Conselho Nacional de Desenvolvimento Científico e Tecnológico (CNPq)

Green Manufacturing: Relationship between Adoption of Green Operational Practices and Green Performance of Brazilian ISO 9001-Certified Firms

The present work aims at analyzing how the adoption of a proactive environmental management via green operational practices (GOPs) correlates to the Green Performance (GrP) of a given set of ISO 9001-certified firms in Brazil. To this end, we elaborated a conceptual framework about environmental management, GOPs, and GrP Such theoretical foundation supported the development of empirical research through quantitative analysis. For the analysis, 75 questionnaires were collected from ISO 9001 certified companies. Data was analyzed by with statistical tools such as descriptive analysis, correlation analysis, and Structural Equation Modeling (SEM). The results demonstrate that the adoption of GOPs, in fact, exerts a positive impact on the GrP of the firms. This work contributes to a better understanding of green manufacturing in Brazil's industrial sector

Performance measurement and indicators for water supply management: review and international cases

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior (CAPES)

Green product development and performance of Brazilian firms: measuring the role of human and technical aspects

The goal of this study is to present and test a conceptual framework that describes the technical aspects (TA), human/organizational aspects (HOA) of the adoption of green product development (GPD) practices and the effect of these practices on firms'environmental (EP), operational (OP) and market performance (MP). To this end, after reviewing the literature on these themes, a conceptual framework with 5 hypotheses is proposed. These hypotheses were tested on 62 Brazilian companies through structural equation modeling using SmartPLS 2.0M3. The main results of this study are as follows: (a) in general, the proposed framework obtained adequate goodness of fit statistics (GoF); (b) technological factors are shown to have an influence on the adoption of GPD practices, and those practices are related to company EP, OP and MP, thus confirming 4 hypotheses of the study; and (c) one of the study's hypotheses is not validated, indicating that the relationship of human/organizational aspects to GPD must be further analyzed. This work extends the literature because: (a) the conceptual framework tested in this study establishes several concepts that have been only partially tested in the previous literature; (b) this work presents evidence about Brazil, where the themes addressed herein have not been yet been thoroughly investigated; and (c) the non-validation of the hypothesis regarding the relationship between human/ organizational aspects with respect to the adoption of product-related environmental practices requires attention. (C) 2014 Elsevier Ltd. All rights reserved.

Análise da performance ambiental e a capacitação profissional rural na produção de soja e milho no estado de Mato Grosso

Pós-graduação em Engenharia de Produção - FEB

A new long-term lifetime distribution induced by a latent complementary risk framework

In this paper, we proposed a new three-parameter long-term lifetime distribution induced by a latent complementary risk framework with decreasing, increasing and unimodal hazard function, the long-term complementary exponential geometric distribution. The new distribution arises from latent competing risk scenarios, where the lifetime associated scenario, with a particular risk, is not observable, rather we observe only the maximum lifetime value among all risks, and the presence of long-term survival. The properties of the proposed distribution are discussed, including its probability density function and explicit algebraic formulas for its reliability, hazard and quantile functions and order statistics. The parameter estimation is based on the usual maximum-likelihood approach. A simulation study assesses the performance of the estimation procedure. We compare the new distribution with its particular cases, as well as with the long-term Weibull distribution on three real data sets, observing its potential and competitiveness in comparison with some usual long-term lifetime distributions.

Delivery Levels of Support Competencies to Organizational Eco-efficiency: a case study in an electro-electronics sector industry

This article aims to develop and implement a search tool which, through the perception of its respondents, allows assessing how eco-efficient an organization is based on the identification of delivery levels of support competencies to organizational eco-efficiency. A mixed (qualitative and quantitative) exploratory-descriptive research was conducted, from a case study in an 'ISE Company'. A semi-structured interview and pictures of verification were used as data collection instruments. The data were analyzed via documentary analysis and triangulation of information collected. It was inferred that at the 'ISE Company' professionals at the high-level of the organizational hierarchy recognize, in part, the growth of organizational actions that contribute to sustainability, which is not fully consistent with national publications on the subject. The result of the research showed that organizational strategies addressing eco-efficiency are partially aligned with the professional performance of the organization.

A novel XML document structure comparison framework based-on sub-tree commonalities and label semantics

XML similarity evaluation has become a central issue in the database and information communities, its applications ranging over document clustering, version control, data integration and ranked retrieval. Various algorithms for comparing hierarchically structured data, XML documents in particular, have been proposed in the literature. Most of them make use of techniques for finding the edit distance between tree structures, XML documents being commonly modeled as Ordered Labeled Trees. Yet, a thorough investigation of current approaches led us to identify several similarity aspects, i.e., sub-tree related structural and semantic similarities, which are not sufficiently addressed while comparing XML documents. In this paper, we provide an integrated and fine-grained comparison framework to deal with both structural and semantic similarities in XML documents (detecting the occurrences and repetitions of structurally and semantically similar sub-trees), and to allow the end-user to adjust the comparison process according to her requirements. Our framework consists of four main modules for (i) discovering the structural commonalities between sub-trees, (ii) identifying sub-tree semantic resemblances, (iii) computing tree-based edit operations costs, and (iv) computing tree edit distance. Experimental results demonstrate higher comparison accuracy with respect to alternative methods, while timing experiments reflect the impact of semantic similarity on overall system performance.

PERFORMANCE EVALUATION OF RESOURCE-AWARE BUSINESS PROCESSES USING STOCHASTIC AUTOMATA NETWORKS

In this work, we study the performance evaluation of resource-aware business process models. We define a new framework that allows the generation of analytical models for performance evaluation from business process models annotated with resource management information. This framework is composed of a new notation that allows the specification of resource management constraints and a method to convert a business process specification and its resource constraints into Stochastic Automata Networks (SANs). We show that the analysis of the generated SAN model provides several performance indices, such as average throughput of the system, average waiting time, average queues size, and utilization rate of resources. Using the BP2SAN tool - our implementation of the proposed framework - and a SAN solver (such as the PEPS tool) we show through a simple use-case how a business specialist with no skills in stochastic modeling can easily obtain performance indices that, in turn, can help to identify bottlenecks on the model, to perform workload characterization, to define the provisioning of resources, and to study other performance related aspects of the business process.

Organization Performance Evaluation Using System Thinking: A Study in Brazilian Chemical Organizations Models

System thinking allows companies to use subjective constructs indicators like recursiveness, cause-effect relationships and autonomy to performance evaluation. Thus, the question that motivates this paper is: Are Brazilian companies searching new performance measurement and evaluation models based on system thinking? The study investigates models looking for system thinking roots in their framework. It was both exploratory and descriptive based on a multiple four case studies strategy in chemical sector. The findings showed organizational models have some characteristics that can be related to system thinking as system control and communication. Complexity and autonomy are deficiently formalized by the companies. All data suggest, inside its context, that system thinking seems to be adequate to organizational performance evaluation but remains distant from the management proceedings.

Incorporating label dependency into the binary relevance framework for multi-label classification

In multi-label classification, examples can be associated with multiple labels simultaneously. The task of learning from multi-label data can be addressed by methods that transform the multi-label classification problem into several single-label classification problems. The binary relevance approach is one of these methods, where the multi-label learning task is decomposed into several independent binary classification problems, one for each label in the set of labels, and the final labels for each example are determined by aggregating the predictions from all binary classifiers. However, this approach fails to consider any dependency among the labels. Aiming to accurately predict label combinations, in this paper we propose a simple approach that enables the binary classifiers to discover existing label dependency by themselves. An experimental study using decision trees, a kernel method as well as Naive Bayes as base-learning techniques shows the potential of the proposed approach to improve the multi-label classification performance.