Globalization and productivity : a survey of firm-level analysis

Recent empirical studies which utilize plant- or establishment-level data to examine globalization's impact on productivity have discovered many causal mechanisms involved in globalization's impact on firms' productivity. Since these pathways have been broad, there have been few attempts to summarize the several and detailed mechanisms of self-selection and learning at the same time. This paper examines seven pathways so that the clear-cut consequences of the broad picture of globalization become visible. This strategy is useful for detecting missing links within and across the existing studies as well as for finding possible synergy effects among different mechanisms. Insightful policy implications may be derived from the comprehensive comparisons between the seven different pathways of globalization.

China's regional economies and value chains : an interregional input-output analysis

Attempts to understand China’s role in global value chains have often noted the case of Apple's iPhone production, in particular the fact that the value added during the Chinese portion of the iPhone’s supply chain is no more than 4%. However, when we examine the Chinese economy as a whole in global production networks, China’s share in total induced value added by China’s exports of final products to the USA is about 75% in 2005. This leads us to investigate how Chinese value added is created and distributed not only internationally but also domestically. To elucidate the increasing complexity of China’s domestic production networks, this paper focuses on the measure of Domestic Value Chains (DVCs) across regions and their linkages with global markets. By using China’s 1997 and 2007 interregional input-output tables, we can understand in detail the structural changes in domestic trade in terms of value added, as well as the position and degree of participation of different regions within the DVCs.

Formation of supply chain collaboration and firm performance in the Thai automotive and electronics industries

This paper examines factors that encourage firms to go into supply chain collaborations (SCC) and relationships between SCC and supply chain performances (SCP), using a questionnaire survey on Thai automotive and electronics industries in 2012. OLS regression results show firms established supplier evaluation and audit system, system of rewards for high-performance supplier and long-term transactions with their supply chain partners under a competitive pressure are more closely cooperate with these partners on information sharing and decision synchronization. Instrumental variables regression indicates SCC arisen from competitive pressure, supplier evaluation and audit, a system of rewards for high-performance supplier and long-term relationship causally influence SCP such as on-time delivery, responsiveness to fast procurement, flexibility to customer need, and profit.

Supply chain collaboration and responsiveness : a comparison between Thai automotive and electronics industries

This paper examines factors that promote firms to develop supply chain collaborations (SCC) with their partners and relationships between SCC and supply chain operational performances (SCOP), using a questionnaire survey on Thai automotive and electronics industries in 2012. This paper also carries out a comparative study on these questions between the electronics and automotive industries. Two-stage least squares (2SLS) regressions verifY that supplier evaluation and audit is a foundation for firms to share information and synchronize decision makings with their partners, and that such SCC are significantly related to SCOP indictors such as on-time delivery, fast procurement, and flexibility to customer need irrespective of industry type. On the other hand, competitive pressure motivates only electronics firms to develop sec in order to be more innovative.

Adoption of ISO9001 through supply chain in Vietnam : impacts of FDI and product-related environmental regulation

The objective of the present study is to examine the determinants of ISO 9001 certification, focusing on the effect of Product-related Environmental Regulations on Chemicals (PRERCs) and FDI using the answers to several questions in our Vietnam survey conducted from December 2011 to January 2012. Our findings suggest that PRERCs may help with the improvement in quality control of Vietnamese firms. If Vietnamese manufacturing firms with ISO 9001 certification are more likely to adopt ISO 14001, as well as firms in developed countries, our results indicate that the European chemical regulations may assist in the reduction of various environmental impacts in Vietnam. In addition, we found that FDI promotes the adoption of ISO 9001. If FDI firms in Vietnam certify ISO 14001 after the adoption of ISO 9001, as in the case of Malaysia and the developed economies, FDI firms may also be able to improve environmental performance as a result of ISO 14001.

Japanese import survey : descriptive analysis

Food importers, such as wholesalers and food processing firms, play an important role in sourcing food from abroad. They are also responsible for ensuring that imported food meets the food safety standards of the importing country. Often, assurance of conformity is done in collaboration with exporters. Thus, importers can influence how supply chains in developing countries are organized. This paper uses a unique dataset obtained from the Japanese market to examine how importers select suppliers and assure food quality.

Governance Structure Choices in Supply Chain Management Evidence from Spanish and Chinese Pork Chain Cases

The author participated in the 6 th EU Framework Project ―Q-pork Chains (FP6-036245-2)‖ from 2007 to 2009. With understanding of work reports from China and other countries, it is found that compared with other countries, China has great problems in pork quality and safety. By comparing the pork chain management between China and Spain, It is found that the difference in governance structure is one of the main differences in pork chain management between Spain and China. In China, spot-market relationship still dominates governance structure of pork chain, especially between the numerous house-hold pig holders and the great number of small slaughters. While in Spain, chain agents commonly apply cooperatives or integrations to cooperate. It also has been proven by recent studies, that in quality management at the chain level that supply chain integration has a direct effect on quality management practices (Han, 2010). Therefore, the author started to investigate the governance structure choices in supply chain management. And it has been set as the first research objective, which is to explain the governance structure choices process and the influencing factors in supply chain management, analyzing the pork chains cases in Spain and in China. During the further investigation, the author noticed the international trade of pork between Spain and China is not smooth since the signature of bi-lateral agreement on pork trade in 2007. Thus, another objective of the research is to find and solve the problems exist in the international pork chain between Spain and China. For the first objective, to explain the governance structure choices in supply chain management, the thesis conducts research in three main sections. 10 First of all, the thesis gives a literature overview in chapter two on Supply Chain Management (SCM), agri-food chain management and pork chain management. It concludes that SCM is a systems approach to view the supply chains as a whole, and to manage the total flow of goods inventory from the supplier to the ultimate customer. It includes the bi-directional flow of products (materials and services) and information, and the associated managerial and operational activities. And it also is a customer focus to create unique and individual source of customer value with an appropriate use of resources, leading to customer satisfaction and building competitive chain advantages. Agri-food chain management and pork chain management are applications of SCM in agri-food sector and pork sector respectively. Then, the research gives a comparative study in chapter three in the pork chain and pork chain management between Spain and China. Many differences are found, while the main difference is governance structure in pork chain management. Furthermore, the author gives an empirical study on governance structure choice in chapter five. It is concluded that governance structure of supply chain consists of a collection of rules/institutions/constraints structuring the transactions between the various stakeholders. Based on the overview on literatures closely related with governance structure, such as transaction cost economics, transaction value analysis and resource-based view theories, seven hypotheses are proposed, which are: Hypothesis 1: Transaction cost has positive relationship with governance structure choice Hypothesis 2: Uncertainty has positive relationship with transaction cost; higher uncertainty exerts high transaction cost Hypothesis 3: The relationship between asset specificity and transaction cost is positive Hypothesis 4: Collaboration advantages and governance structure choice have positive relationship11 Hypothesis 5: Willingness to collaborate has positive relationship with collaboration advantages Hypothesis 6: Capability to collaborate has positive relationship with collaboration advantages Hypothesis 7: Uncertainty has negative effect on collaboration advantages It is noted that as transaction cost value is negative, the transaction cost mentioned in the hypotheses is its absolute value. To test the seven hypotheses, Structural Equation Model (SEM) is applied and data collected from 350 pork slaughtering and processing companies in Jiangsu, Shandong and Henan Provinces in China is used. Based on the empirical SEM model and its results, the seven hypotheses are proved. The author generates several conclusions accordingly. It is found that the governance structure choice of the chain not only depends on transaction cost, it also depends on collaboration advantages. Exchange partners establish more stable and more intense relationship to reduce transaction cost and to maximize collaboration advantages. ―Collaboration advantages‖ in this thesis is defined as the joint value achieved through transaction (mutual activities) of agents in supply chains. This value forms as improvements, mainly in mutual logistics systems, cash response, information exchange, technological improvements and innovative improvements and quality management improvements, etc. Governance structure choice is jointly decided by transaction cost and collaboration advantages. Chain agents take different governance structures to coordinate in order to decrease their transaction cost and to increase their collaboration advantages. In China´s pork chain case, spot market relationship dominates the governance structure among the numerous backyard pig farmer and small family slaughterhouse 12 as they are connected by acquaintance relationship and the transaction cost in turn is low. Their relationship is reliable as they know each other in the neighborhood; as a result, spot market relationship is suitable for their exchange. However, the transaction between large-scale slaughtering and processing industries and small-scale pig producers is becoming difficult. The information hold back behavior and hold-up behavior of small-scale pig producers increase transaction cost between them and large-scale slaughtering and processing industries. Thus, through the more intense and stable relationship between processing industries and pig producers, processing industries reduce the transaction cost and improve the collaboration advantages with their chain partners, in which quality and safety collaboration advantages be increased, meaning that processing industries are able to provide consumers products with better quality and higher safety. It is also drawn that transaction cost is influenced mainly by uncertainty and asset specificity, which is in line with new institutional economics theories developed by Williamson O. E. In China´s pork chain case, behavioral uncertainty is created by the hold-up behaviors of great numbers of small pig producers, while big slaughtering and processing industries having strong asset specificity. On the other hand, ―collaboration advantages‖ is influenced by chain agents´ willingness to collaborate and chain agents´ capabilities to cooperate. With the fast growth of big scale slaughtering and processing industries, they are more willing to know and make effort to cooperate with their chain members, and they are more capable to create joint value together with other chain agents. Therefore, they are now the main chain agents who drive more intense and stable governance structure in China‘s pork chain. For the other objective, to find and solve the problems in the international pork chain between Spain and China, the research gives an analysis in chapter four on the 13 international pork chain. This study gives explanations why the international trade of pork between Spain and China is not sufficient from the chain perspective. It is found that the first obstacle is the high quality and safety requirement set by Chinese government. It makes the Spanish companies difficult to get authorities to export. Other aspects, such as Spanish pork is not competitive in price compared with other countries such as Denmark, United States, Canada, etc., Chinese consumers do not have sufficient information on Spanish pork products, are also important reasons that Spain does not export great quantity of pork products to China. It is concluded that China´s government has too much concern on the quality and safety requirements to Spanish pork products, which makes trade difficult to complete. The two countries need to establish a more stable and intense trade relationship. They also should make the information exchange sufficient and efficient and try to break trade barriers. Spanish companies should consider proper price strategies to win the Chinese pork market

Video analysis based vehicle detection and tracking using an MCMC sampling framework

This article presents a probabilistic method for vehicle detection and tracking through the analysis of monocular images obtained from a vehicle-mounted camera. The method is designed to address the main shortcomings of traditional particle filtering approaches, namely Bayesian methods based on importance sampling, for use in traffic environments. These methods do not scale well when the dimensionality of the feature space grows, which creates significant limitations when tracking multiple objects. Alternatively, the proposed method is based on a Markov chain Monte Carlo (MCMC) approach, which allows efficient sampling of the feature space. The method involves important contributions in both the motion and the observation models of the tracker. Indeed, as opposed to particle filter-based tracking methods in the literature, which typically resort to observation models based on appearance or template matching, in this study a likelihood model that combines appearance analysis with information from motion parallax is introduced. Regarding the motion model, a new interaction treatment is defined based on Markov random fields (MRF) that allows for the handling of possible inter-dependencies in vehicle trajectories. As for vehicle detection, the method relies on a supervised classification stage using support vector machines (SVM). The contribution in this field is twofold. First, a new descriptor based on the analysis of gradient orientations in concentric rectangles is dened. This descriptor involves a much smaller feature space compared to traditional descriptors, which are too costly for real-time applications. Second, a new vehicle image database is generated to train the SVM and made public. The proposed vehicle detection and tracking method is proven to outperform existing methods and to successfully handle challenging situations in the test sequences.

Upper Limb Portable Motion Analysis System Based on Inertial Technology for Neurorehabilitation Purposes

Here an inertial sensor-based monitoring system for measuring and analyzing upper limb movements is presented. The final goal is the integration of this motion-tracking device within a portable rehabilitation system for brain injury patients. A set of four inertial sensors mounted on a special garment worn by the patient provides the quaternions representing the patient upper limb’s orientation in space. A kinematic model is built to estimate 3D upper limb motion for accurate therapeutic evaluation. The human upper limb is represented as a kinematic chain of rigid bodies with three joints and six degrees of freedom. Validation of the system has been performed by co-registration of movements with a commercial optoelectronic tracking system. Successful results are shown that exhibit a high correlation among signals provided by both devices and obtained at the Institut Guttmann Neurorehabilitation Hospital.

Genome-Wide Analysis of the Response of Dickeya dadantii 3937 to Plant Antimicrobial Peptides

Antimicrobial peptides constitute an important factor in the defense of plants against pathogens, and bacterial resistance to these peptides have previously been shown to be an important virulence factor in Dickeya dadantii, the causal agent of soft-rot disease of vegetables. In order to understand the bacterial response to antimicrobial pep- tides, a transcriptional microarray analysis was performed upon treatment with sub-lethal concentration of thionins, a widespread plant peptide. In all, 36 genes were found to be overexpressed, and were classified according to their deduced function as i) transcriptional regulators, ii) transport, and iii) modification of the bacterial membrane. One gene encoding a uricase was found to be repressed. The majority of these genes are known to be under the control of the PhoP/PhoQ system. Five genes representing the different functions induced were selected for further analysis. The results obtained indicate that the presence of antimicrobial peptides induces a complex response which includes peptide-specific elements and general stress-response elements contributing differentially to the virulence in different hosts.

Image analysis by moment invariants using a set of step-like basis functions

Moment invariants have been thoroughly studied and repeatedly proposed as one of the most powerful tools for 2D shape identification. In this paper a set of such descriptors is proposed, being the basis functions discontinuous in a finite number of points. The goal of using discontinuous functions is to avoid the Gibbs phenomenon, and therefore to yield a better approximation capability for discontinuous signals, as images. Moreover, the proposed set of moments allows the definition of rotation invariants, being this the other main design concern. Translation and scale invariance are achieved by means of standard image normalization. Tests are conducted to evaluate the behavior of these descriptors in noisy environments, where images are corrupted with Gaussian noise up to different SNR values. Results are compared to those obtained using Zernike moments, showing that the proposed descriptor has the same performance in image retrieval tasks in noisy environments, but demanding much less computational power for every stage in the query chain.

On-road visual vehicle tracking using Markov chain Monte Carlo with metropolis sampling

In this study, a method for vehicle tracking through video analysis based on Markov chain Monte Carlo (MCMC) particle filtering with metropolis sampling is proposed. The method handles multiple targets with low computational requirements and is, therefore, ideally suited for advanced-driver assistance systems that involve real-time operation. The method exploits the removed perspective domain given by inverse perspective mapping (IPM) to define a fast and efficient likelihood model. Additionally, the method encompasses an interaction model using Markov Random Fields (MRF) that allows treatment of dependencies between the motions of targets. The proposed method is tested in highway sequences and compared to state-of-the-art methods for vehicle tracking, i.e., independent target tracking with Kalman filtering (KF) and joint tracking with particle filtering. The results showed fewer tracking failures using the proposed method.

Road fright transport decoupling: A comparative analysis between the United Kingdom and Spain

Economic growth has traditionally been linked to road freight transport demand, leading to a steady rise in social and environmental impacts. Concern about this problem has caused the EU to promote a decoupling strategy aimed at boosting sustainable development in European countries by improving the efficiency of transport systems without curbing economic growth. Over the last few years empirical evidence in some countries such as the United Kingdom has shown an increase in GDP while the volume of road freight traffic has remained stable or even decreased. This paper compares recent decoupling trends by analyzing the evolution of road tonne-kms/GDP relationship in the United Kingdom and Spain from 1999 to 2007. This comparison seeks to identify the main differences and key drivers of decoupling in both countries. We first provide an overview of the divergences between both economic structures and levels of road transport intensity. Then we conduct a decomposition analysis in order to identify the variables that explain the evolution of truck traffic per unit of GDP in each country. The results show that the increasing share of services in GDP has substantially contributed to decreasing road transport demand in both cases. Changes in road transport intensity due to improvements in logistic and supply chain management have been more successful in the UK than in Spain.

Expressive power of binary relevance and chain classifiers based on Bayesian Networks for multi-label classification

Bayesian network classifiers are widely used in machine learning because they intuitively represent causal relations. Multi-label classification problems require each instance to be assigned a subset of a defined set of h labels. This problem is equivalent to finding a multi-valued decision function that predicts a vector of h binary classes. In this paper we obtain the decision boundaries of two widely used Bayesian network approaches for building multi-label classifiers: Multi-label Bayesian network classifiers built using the binary relevance method and Bayesian network chain classifiers. We extend our previous single-label results to multi-label chain classifiers, and we prove that, as expected, chain classifiers provide a more expressive model than the binary relevance method.

Detection and quantification of peanut traces in wheat flour by near infrared hyperspectral imaging spectroscopy using principal-component analysis

The use of a common environment for processing different powder foods in the industry has increased the risk of finding peanut traces in powder foods. The analytical methods commonly used for detection of peanut such as enzyme-linked immunosorbent assay (ELISA) and real-time polymerase chain reaction (RT-PCR) represent high specificity and sensitivity but are destructive and time-consuming, and require highly skilled experimenters. The feasibility of NIR hyperspectral imaging (HSI) is studied for the detection of peanut traces down to 0.01% by weight. A principal-component analysis (PCA) was carried out on a dataset of peanut and flour spectra. The obtained loadings were applied to the HSI images of adulterated wheat flour samples with peanut traces. As a result, HSI images were reduced to score images with enhanced contrast between peanut and flour particles. Finally, a threshold was fixed in score images to obtain a binary classification image, and the percentage of peanut adulteration was compared with the percentage of pixels identified as peanut particles. This study allowed the detection of traces of peanut down to 0.01% and quantification of peanut adulteration from 10% to 0.1% with a coefficient of determination (r2) of 0.946. These results show the feasibility of using HSI systems for the detection of peanut traces in conjunction with chemical procedures, such as RT-PCR and ELISA to facilitate enhanced quality-control surveillance on food-product processing lines.