Knowledge effect on firm performance in manufacturing and service firms

This thesis seeks to examine the difference between manufacturing and service firms with respect to the effects of knowledge on performance, and the influence of market turbulence in this relationship. Empirical data, resulting from a survey, was collected from more than 1,206 firms, involving several sectors. Two samples were analyzed, one with 334 manufacturing and other with 509 service firms. The findings indicate no significant difference in the importance of knowledge on performance between these sectors in the absence of market turbulence: knowledge development (KD) has a stronger effect than culture of competitiveness (CC) on firm performance. However, under market turbulence, manufacturers differ from service providers. The positive effect of KD is enhanced, while the positive effect of CC remains the same for manufacturing firms. On the other hand, the positive effect of KD is diminished, while the positive effect of CC is enhanced for service firms. This supports the argument concerning differences in the nature of manufacturing and service industries. From a managerial point of view, results confirm the importance of knowledge, irrespective of firm sector or market turbulence. However, while industrial firms should center efforts on KD, service firms must find a balance where knowledge development (e.g. norms, processes, routines) does not impair their culture of competitiveness (e.g. learning, innovation, action). The thesis contributes to existing literature by proposing that: (1) the positive effect of knowledge on performance is confirmed; (2) under turbulent markets manufacturing and service firms have different responses concerning the influence of knowledge on performance; (3) a multidimensional performance construct based on cost, profitability, and growth is an interesting way to evaluate firm sustained competitive advantage, rather than one-dimensional constructs; (4) the CC x KD interaction, found relevant for supply chains in previous studies, is not supported for firms; (5) differences in unit of analysis, e.g. from supply chains to firms, result in different effects of KD and CC on firm performance; (6) existing scales can be improved with the addition of more diverse indicators, capturing a wider range of concepts (e.g. information transfer measurement); and (7) results from previous studies are supported for Brazilian firms, contributing for theory generalization.

The role of profits in wage determination: evidence from US manufacturing

We estimate the effect of firms' profitability on wage determination for the American economy. Two standard bargaining models are used to illustrate the problems caused by the endogeneity of profits-per-worker in a real wage equation. The profit-sharing parameter can be identified with instruments which shift demando Using information from the input-output table, we create demand-shift variables for 63 4-digit sectors of the US manufacturing sector. The LV. estimates show that profit-sharing is a relevant and widespread phenomenon. The elasticity of wages with respect to profits-per-worker is seven times as large as OLS estimates here and in previous papers. Sensitivity analysis of the profit-sharing parameter controlling for the extent of unionization and product market concentration reinforces our results.

A restatement of the welafare costs of inflation. The wast of scarce resources in the manufacturing , banking and household sectors

Lucas (2000) estimates that the US welfare costs of inflation are around 1% of GDP. This measurement is consistent with a speci…c distorting channel in terms of the Bailey triangle under the demand for monetary base schedule (outside money): the displacement of resources from the production of consumption goods to the household transaction time à la Baumol. Here, we consider also several new types of distortions in the manufacturing and banking industries. Our new evidences show that both banks and firms demand special occupational employments to avoid the inflation tax. We de…ne the concept of ”the foat labor”: The occupational employments that are aflected by the in‡ation rates. More administrative workers are hired relatively to the bluecollar workers for producing consumption goods. This new phenomenon makes the manufacturing industry more roundabout. To take into account this new stylized fact and others, we redo at same time both ”The model 5: A Banking Sector -2” formulated by Lucas (1993) and ”The Competitive Banking System” proposed by Yoshino (1993). This modelling allows us to characterize better the new types of misallocations. We …nd that the maximum value of the resources wasted by the US economy happened in the years 1980-81, after the 2nd oil shock. In these years, we estimate the excess resources that are allocated for every speci…c distorting channel: i) The US commercial banks spent additional resources of around 2% of GDP; ii) For the purpose of the firm foating time were used between 2.4% and 4.1% of GDP); and iii) For the household transaction time were allocated between 3.1% and 4.5 % of GDP. The Bailey triangle under the demand for the monetary base schedule represented around 1% of GDP, which is consistent with Lucas (2000). We estimate that the US total welfare costs of in‡ation were around 10% of GDP in terms of the consumption goods foregone. The big di¤erence between our results and Lucas (2000) are mainly due to the Harberger triangle in the market for loans (inside money) which makes part of the household transaction time, of the …rm ‡oat labor and of the distortion in the banking industry. This triangle arises due to the widening interest rates spread in the presence of a distorting inflation tax and under a fractionally reserve system. The Harberger triangle can represent 80% of the total welfare costs of inflation while the remaining percentage is split almost equally between the Bailey triangle and the resources used for the bank services. Finally, we formulate several theorems in terms of the optimal nonneutral monetary policy so as to compare with the classical monetary theory.

The manufacturing industry in Brazil in the era of global value chains

This article presents a comprehensive and detailed overview of the international trade performance of the manufacturing industry in Brazil over the last decades, emphasizing its participation in Global Value Chains. It uses information from recent available global inputoutput tables such as WIOD (World Input-output database) and TIVA (Trade in Value Added, OECD) as well as complementary information from the GTAP 8 (Global Trade Analysis Project) database. The calculation of a broad set of value added type indicators allows a precise contextualization of the ongoing structural changes in the Brazilian industry, highlighting the relative isolation of its manufacturing sector from the most relevant international supply chains. This article also proposes a public policy discussion, presenting two case studies: the first one related to trade facilitation and the second one to preferential trade agreements. The main conclusions are twofold: first, the reduction of time delays at customs in Brazil may significantly improve the trade performance of its manufacturing industry, specially for the more capital intensive sectors which are generally the ones with greater potential to connection to global value chains; second, the extension of the concept of a “preferential trade partner” to the context of the global unbundling of production may pave the way to future trade policy in Brazil, particularly in the mapping of those partners whose bilateral trade relations with Brazil should receive greater priority by policy makers.

The manufacturing industry in Brazil in the era of global value chains

This article presents a comprehensive and detailed overview of the international trade performance of the manufacturing industry in Brazil over the last decades, emphasizing its participation in Global Value Chains. It uses information from recent available global inputoutput tables such as WIOD (World Input-output database) and TIVA (Trade in Value Added, OECD) as well as complementary information from the GTAP 8 (Global Trade Analysis Project) database. The calculation of a broad set of value added type indicators allows a precise contextualization of the ongoing structural changes in the Brazilian industry, highlighting the relative isolation of its manufacturing sector from the most relevant international supply chains. This article also proposes a public policy discussion, presenting two case studies: the first one related to trade facilitation and the second one to preferential trade agreements. The main conclusions are twofold: first, the reduction of time delays at customs in Brazil may significantly improve the trade performance of its manufacturing industry, specially for the more capital intensive sectors which are generally the ones with greater potential to connection to global value chains; second, the extension of the concept of a “preferential trade partner” to the context of the global unbundling of production may pave the way to future trade policy in Brazil, particularly in the mapping of those partners whose bilateral trade relations with Brazil should receive greater priority by policy makers

Comparative analysis between a CAD model design and physical models obtained by manufacturing additive technologies using optical scan

This article presents a detailed study of the application of different additive manufacturing technologies (sintering process, three-dimensional printing, extrusion and stereolithographic process), in the design process of a complex geometry model and its moving parts. The fabrication sequence was evaluated in terms of pre-processing conditions (model generation and model STL SLI), generation strategy and physical model post-processing operations. Dimensional verification of the obtained models was undertook by projecting structured light (optical scan), a relatively new technology of main importance for metrology and reverse engineering. Studies were done in certain manufacturing time and production costs, which allowed the definition of an more comprehensive evaluation matrix of additive technologies.

An Intelligent System for Petroleum Well Drilling Cutting Analysis

Cutting analysis is a important and crucial task task to detect and prevent problems during the petroleum well drilling process. Several studies have been developed for drilling inspection, but none of them takes care about analysing the generated cutting at the vibrating shale shakers. Here we proposed a system to analyse the cutting's concentration at the vibrating shale shakers, which can indicate problems during the petroleum well drilling process, such that the collapse of the well borehole walls. Cutting's images are acquired and sent to the data analysis module, which has as the main goal to extract features and to classify frames according to one of three previously classes of cutting's volume. A collection of supervised classifiers were applied in order to allow comparisons about their accuracy and efficiency. We used the Optimum-Path Forest (OPF), Artificial Neural Network using Multi layer Perceptrons (ANN-MLP), Support Vector Machines (SVM) and a Bayesian Classifier (BC) for this task. The first one outperformed all the remaining classifiers. Recall that we are also the first to introduce the OPF classifier in this field of knowledge. Very good results show the robustness of the proposed system, which can be also integrated with other commonly system (Mud-Logging) in order to improve the last one's efficiency.

Application of intelligent systems for specification of automotive equipments using LEDs

The advantages offered by the electronic component light emitting diode ( LED) have caused a quick and wide application of this device in replacement of incandescent lights. However, in its combined application, the relationship between the design variables and the desired effect or result is very complex and it becomes difficult to model by conventional techniques. This work consists of the development of a technique, through artificial neural networks, to make possible to obtain the luminous intensity values of brake lights using LEDs from design data. (C) 2005 Elsevier B.V. All rights reserved.

A novel intelligent system to nitrogen content prediction in plants using indirect chlorophyll measurements

The accurate identification of the nitrogen content in plants is extremely important since it involves economic aspects and environmental impacts, Several experimental tests have been carried out to obtain characteristics and parameters associated with the health of plants and its growing. The nitrogen content identification in plants involves a lot of non-linear parameters and complexes mathematical models. This paper describes a novel approach for identification of nitrogen content thought SPAD index using artificial neural networks (ANN). The network acts as identifier of relationships among, crop varieties, fertilizer treatments, type of leaf and nitrogen content in the plants (target). So, nitrogen content can be generalized and estimated and from an input parameter set. This approach can form the basis for development of an accurate real time system to predict nitrogen content in plants.

Automatic detection of thermal damage in grinding process by artificial neural network

Esse trabalho tem por objetivo o desenvolvimento de um sistema inteligente para detecção da queima no processo de retificação tangencial plana através da utilização de uma rede neural perceptron multi camadas, treinada para generalizar o processo e, conseqüentemente, obter o limiar de queima. em geral, a ocorrência da queima no processo de retificação pode ser detectada pelos parâmetros DPO e FKS. Porém esses parâmetros não são eficientes nas condições de usinagem usadas nesse trabalho. Os sinais de emissão acústica e potência elétrica do motor de acionamento do rebolo são variáveis de entrada e a variável de saída é a ocorrência da queima. No trabalho experimental, foram empregados um tipo de aço (ABNT 1045 temperado) e um tipo de rebolo denominado TARGA, modelo ART 3TG80.3 NVHB.

Analysis of forecasting capabilities of ground surfaces valuation using artificial neural networks

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

Beam Search Algorithms for Minimizing Tool Switches on a Flexible Manufacturing System

In the minimization of tool switches problem we seek a sequence to process a set of jobs so that the number of tool switches required is minimized. In this work different variations of a heuristic based on partial ordered job sequences are implemented and evaluated. All variations adopt a depth first strategy of the enumeration tree. The computational test results indicate that good results can be obtained by a variation which keeps the best three branches at each node of the enumeration tree, and randomly choose, among all active nodes, the next node to branch when backtracking.

Design of a reconfigurable pseudorandom number generator for use in intelligent systems

This paper deals with the design of a network-on-chip reconfigurable pseudorandom number generation unit that can map and execute meta-heuristic algorithms in hardware. The unit can be configured to implement one of the following five linear generator algorithms: a multiplicative congruential, a mixed congruential, a standard multiple recursive, a mixed multiple recursive, and a multiply-with-carry. The generation unit can be used both as a pseudorandom and a message passing-based server, which is able to produce pseudorandom numbers on demand, sending them to the network-on-chip blocks that originate the service request. The generator architecture has been mapped to a field programmable gate array, and showed that millions of numbers in 32-, 64-, 96-, or 128-bit formats can be produced in tens of milliseconds. (C) 2011 Elsevier B.V. All rights reserved.