Public enterprise reforms and efficiency in regulated environments: the case of the postal sector

Purpose - This paper focuses on analyzing the effect that public reforms have on the efficiency of state-owned enterprises in regulated environments. Design/methodology/approach - The research is focused in the postal sector where public and private companies must obey a legal framework related to provide a universal service. The analysis is carried out using a panel of 7 European postal operators for the period 1997-2003. The activity analyzed was the letter mail division; we take as key variable the unit cost of a letter and use a translog cost function where as independent variables we include traffic levels, labor cost per employee, quality and availability of the service as well as the type of ownership (public or private). Additionally, in a second stage the geographical differences among countries are considered. Findings - Results indicate that postal operators that experienced organizational changes without being privatized, such as the Spanish and Greek operators, do not have higher unit costs than privatized postal operators like the one of Germany and the Netherlands. Moreover, we find that in all cases the operator of Ireland appear to be the most efficient. In this case restructuring process has been carried out giving an important leadership role to workers. This suggests us that labor culture could be a key variable to study when analyzing reform processes in public enterprises. Originality/value - Our findings show that in a regulated environment like in the postal sector, public and private companies can obtain similar efficiency levels in term of unit costs.

Origins and efficiency of the electric industry regulation in Spain, 1910-1936

The aim of this paper is to discover the origins of utility regulation in Spain, and to analyse, from a microeconomic perspective, its characteristics and the impact of regulation on consumers and utilities. Madrid and the Madrilenian utilities are taken as a case study. The electric industry in the period studied was a natural monopoly2. Each of the three phases of production, generation, transmission and distribution, had natural monopoly characteristics. Therefore, the most efficient form to generate, transmit and distribute electricity was the monopoly because one firm can produce a quantity at a lower cost than the sum of costs incurred by two or more firms. A problem arises because when a firm is the single provider it can charge prices above the marginal cost, at monopoly prices. When a monopolist reduces the quantity produced, price increases, causing the consumer to demand less than the economic efficiency level, incurring a loss of consumer surplus. The loss of the consumer surplus is not completely gained by the monopolist, causing a loss of social surplus, a deadweight loss. The main objective of regulation is going to be to reduce to a minimum the deadweight loss. Regulation is also needed because when the monopolist fixes prices at marginal cost equal marginal revenue there would be an incentive for firms to enter the market creating inefficiency. The Madrilenian industry has been chosen because of the availability of statistical information on costs and production. The complex industry structure and the atomised demand add interest to the analysis. This study will also provide some light on the tariff regulation of the period which has been poorly studied and will complement the literature on the US electric utilities regulation where a different type of regulation was implemented.

Availability and use of organic matter in stream ecosystems: the role of biofilms

La comunitat bentònica dels ecosistemes fluvials processa una gran quantitat de la matèria orgànica que arriba als rius. L'origen de les entrades de material (autòctones o al·lòctones), la seva composició química i la seva quantitat (freqüència de les entrades i concentració assolida en el riu), determinen l'estructura de la comunitat bentònica autotròfica i heterotròfica, les seves relacions tròfiques i les seves interaccions potencials (competència, sinergisme). L'objectiu d'aquesta tesi és posar de manifest la utilització de la matèria orgànica dissolta (MOD) per part dels biofilms bacterians bentònics fluvials i determinar l'eficiència del sistema fluvial en l'ús dels diferents materials que hi circulen. Amb aquesta finalitat s'han portat a terme diversos experiments, tant de camp com de laboratori, per tal de conèixer els efectes de la disponibilitat de la matèria orgànica (quantitat) i la seva qualitat (composició química i biodegradabilitat) i els efectes deguts a l'augment de temperatura de l'aigua del riu.

Resource availability and the persistence of seed-eating bird populations in agricultural landscapes – a mechanistic modelling approach

1. Reductions in resource availability, associated with land-use change and agricultural intensification in the UK and Europe, have been linked with the widespread decline of many farmland bird species over recent decades. However, the underlying ecological processes which link resource availability and population trends are poorly understood. 2. We construct a spatial depletion model to investigate the relationship between the population persistence of granivorous birds within the agricultural landscape and the temporal dynamics of stubble field availability, an important source of winter food for many of those species. 3. The model is capable of accurately predicting the distribution of a given number of finches and buntings amongst patches of different stubble types in an agricultural landscape over the course of a winter and assessing the relative value of different landscapes in terms of resource availability. 4. Sensitivity analyses showed that the model is relatively robust to estimates of energetic requirements, search efficiency and handling time but that daily seed survival estimates have a strong influence on model fit. Understanding resource dynamics in agricultural landscapes is highlighted as a key area for further research. 5. There was a positive relationship between the predicted number of bird days supported by a landscape over-winter and the breeding population trend for yellowhammer Emberiza citrinella, a species for which survival has been identified as the primary driver of population dynamics, but not for linnet Carduelis cannabina, a species for which productivity has been identified as the primary driver of population dynamics. 6. Synthesis and applications. We believe this model can be used to guide the effective delivery of over-winter food resources under agri-environment schemes and to assess the impacts on granivorous birds of changing resource availability associated with novel changes in land use. This could be very important in the future as farming adapts to an increasingly dynamic trading environment, in which demands for increased agricultural production must be reconciled with objectives for environmental protection, including biodiversity conservation.

Comparative gas exchange performance during the wet season of three Brazilian Styrax species under habitat conditions of cerrado vegetation types differing in soil water availability and crown density

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

Utilizing the Internet of Things to promote energy awareness and efficiency at discrete production processes: Practices and methodology

El actual contexto de fabricación, con incrementos en los precios de la energía, una creciente preocupación medioambiental y cambios continuos en los comportamientos de los consumidores, fomenta que los responsables prioricen la fabricación respetuosa con el medioambiente. El paradigma del Internet de las Cosas (IoT) promete incrementar la visibilidad y la atención prestada al consumo de energía gracias tanto a sensores como a medidores inteligentes en los niveles de máquina y de línea de producción. En consecuencia es posible y sencillo obtener datos de consumo de energía en tiempo real proveniente de los procesos de fabricación, pero además es posible analizarlos para incrementar su importancia en la toma de decisiones. Esta tesis pretende investigar cómo utilizar la adopción del Internet de las Cosas en el nivel de planta de producción, en procesos discretos, para incrementar la capacidad de uso de la información proveniente tanto de la energía como de la eficiencia energética. Para alcanzar este objetivo general, la investigación se ha dividido en cuatro sub-objetivos y la misma se ha desarrollado a lo largo de cuatro fases principales (en adelante estudios). El primer estudio de esta tesis, que se apoya sobre una revisión bibliográfica comprehensiva y sobre las aportaciones de expertos, define prácticas de gestión de la producción que son energéticamente eficientes y que se apoyan de un modo preeminente en la tecnología IoT. Este primer estudio también detalla los beneficios esperables al adoptar estas prácticas de gestión. Además, propugna un marco de referencia para permitir la integración de los datos que sobre el consumo energético se obtienen en el marco de las plataformas y sistemas de información de la compañía. Esto se lleva a cabo con el objetivo último de remarcar cómo estos datos pueden ser utilizados para apalancar decisiones en los niveles de procesos tanto tácticos como operativos. Segundo, considerando los precios de la energía como variables en el mercado intradiario y la disponibilidad de información detallada sobre el estado de las máquinas desde el punto de vista de consumo energético, el segundo estudio propone un modelo matemático para minimizar los costes del consumo de energía para la programación de asignaciones de una única máquina que deba atender a varios procesos de producción. Este modelo permite la toma de decisiones en el nivel de máquina para determinar los instantes de lanzamiento de cada trabajo de producción, los tiempos muertos, cuándo la máquina debe ser puesta en un estado de apagada, el momento adecuado para rearrancar, y para pararse, etc. Así, este modelo habilita al responsable de producción de implementar el esquema de producción menos costoso para cada turno de producción. En el tercer estudio esta investigación proporciona una metodología para ayudar a los responsables a implementar IoT en el nivel de los sistemas productivos. Se incluye un análisis del estado en que se encuentran los sistemas de gestión de energía y de producción en la factoría, así como también se proporcionan recomendaciones sobre procedimientos para implementar IoT para capturar y analizar los datos de consumo. Esta metodología ha sido validada en un estudio piloto, donde algunos indicadores clave de rendimiento (KPIs) han sido empleados para determinar la eficiencia energética. En el cuarto estudio el objetivo es introducir una vía para obtener visibilidad y relevancia a diferentes niveles de la energía consumida en los procesos de producción. El método propuesto permite que las factorías con procesos de producción discretos puedan determinar la energía consumida, el CO2 emitido o el coste de la energía consumida ya sea en cualquiera de los niveles: operación, producto o la orden de fabricación completa, siempre considerando las diferentes fuentes de energía y las fluctuaciones en los precios de la misma. Los resultados muestran que decisiones y prácticas de gestión para conseguir sistemas de producción energéticamente eficientes son posibles en virtud del Internet de las Cosas. También, con los resultados de esta tesis los responsables de la gestión energética en las compañías pueden plantearse una aproximación a la utilización del IoT desde un punto de vista de la obtención de beneficios, abordando aquellas prácticas de gestión energética que se encuentran más próximas al nivel de madurez de la factoría, a sus objetivos, al tipo de producción que desarrolla, etc. Así mismo esta tesis muestra que es posible obtener reducciones significativas de coste simplemente evitando los períodos de pico diario en el precio de la misma. Además la tesis permite identificar cómo el nivel de monitorización del consumo energético (es decir al nivel de máquina), el intervalo temporal, y el nivel del análisis de los datos son factores determinantes a la hora de localizar oportunidades para mejorar la eficiencia energética. Adicionalmente, la integración de datos de consumo energético en tiempo real con datos de producción (cuando existen altos niveles de estandarización en los procesos productivos y sus datos) es esencial para permitir que las factorías detallen la energía efectivamente consumida, su coste y CO2 emitido durante la producción de un producto o componente. Esto permite obtener una valiosa información a los gestores en el nivel decisor de la factoría así como a los consumidores y reguladores. ABSTRACT In today‘s manufacturing scenario, rising energy prices, increasing ecological awareness, and changing consumer behaviors are driving decision makers to prioritize green manufacturing. The Internet of Things (IoT) paradigm promises to increase the visibility and awareness of energy consumption, thanks to smart sensors and smart meters at the machine and production line level. Consequently, real-time energy consumption data from the manufacturing processes can be easily collected and then analyzed, to improve energy-aware decision-making. This thesis aims to investigate how to utilize the adoption of the Internet of Things at shop floor level to increase energy–awareness and the energy efficiency of discrete production processes. In order to achieve the main research goal, the research is divided into four sub-objectives, and is accomplished during four main phases (i.e., studies). In the first study, by relying on a comprehensive literature review and on experts‘ insights, the thesis defines energy-efficient production management practices that are enhanced and enabled by IoT technology. The first study also explains the benefits that can be obtained by adopting such management practices. Furthermore, it presents a framework to support the integration of gathered energy data into a company‘s information technology tools and platforms, which is done with the ultimate goal of highlighting how operational and tactical decision-making processes could leverage such data in order to improve energy efficiency. Considering the variable energy prices in one day, along with the availability of detailed machine status energy data, the second study proposes a mathematical model to minimize energy consumption costs for single machine production scheduling during production processes. This model works by making decisions at the machine level to determine the launch times for job processing, idle time, when the machine must be shut down, ―turning on‖ time, and ―turning off‖ time. This model enables the operations manager to implement the least expensive production schedule during a production shift. In the third study, the research provides a methodology to help managers implement the IoT at the production system level; it includes an analysis of current energy management and production systems at the factory, and recommends procedures for implementing the IoT to collect and analyze energy data. The methodology has been validated by a pilot study, where energy KPIs have been used to evaluate energy efficiency. In the fourth study, the goal is to introduce a way to achieve multi-level awareness of the energy consumed during production processes. The proposed method enables discrete factories to specify energy consumption, CO2 emissions, and the cost of the energy consumed at operation, production and order levels, while considering energy sources and fluctuations in energy prices. The results show that energy-efficient production management practices and decisions can be enhanced and enabled by the IoT. With the outcomes of the thesis, energy managers can approach the IoT adoption in a benefit-driven way, by addressing energy management practices that are close to the maturity level of the factory, target, production type, etc. The thesis also shows that significant reductions in energy costs can be achieved by avoiding high-energy price periods in a day. Furthermore, the thesis determines the level of monitoring energy consumption (i.e., machine level), the interval time, and the level of energy data analysis, which are all important factors involved in finding opportunities to improve energy efficiency. Eventually, integrating real-time energy data with production data (when there are high levels of production process standardization data) is essential to enable factories to specify the amount and cost of energy consumed, as well as the CO2 emitted while producing a product, providing valuable information to decision makers at the factory level as well as to consumers and regulators.

Biomass sustainability, availability and productivity

Research conducted on biomass for Ulcos (""Ultra-Low CO(2) Steelmaking"" European Integrated Project) has progressively focused on charcoal supply from tropical eucalyptus plantations. The sustainability of such plantations is being investigated from the viewpoint of their carbon, water and nutrient budgets: they must all be neutral or positive. Field research is producing results at the tree or stand level in several sites of Congo and Brazil, while a spatial model is developed to identify the conditions of biomass neutrality at the scale of the forest ecosystem. The productivity of biomass has been analyzed through the description of practices along the various supply-schemes that competitively feed the steel industry in Brazil and identification of bottlenecks for further expansion.

A twin study of psychometric intelligence and efficiency of information processing

Intelligence (IQ) can be seen as the efficiency of mental processes or cognition, as can basic information processing (IP) tasks like those used in our ongoing Memory, Attention and Problem Solving (MAPS) study. Measures of IQ and IP are correlated and both have a genetic component, so we are studying how the genetic variance in IQ is related to the genetic variance in IP. We measured intelligence with five subscales of the Multidimensional Aptitude Battery (MAB). The IP tasks included four variants of choice reaction time (CRT) and a visual inspection time (IT). The influence of genetic factors on the variances in each of the IQ, IP, and IT tasks was investigated in 250 identical and nonidentical twin pairs aged 16 years. For a subset of 50 pairs we have test–retest data that allow us to estimate the stability of the measures. MX was used for a multivariate genetic analysis that addresses whether the variance in IQ and IP measures is possibly mediated by common genetic factors. Analyses that show the modeled genetic and environmental influences on these measures of cognitive efficiency will be presented and their relevance to ideas on intelligence will be discussed.

Neighborhood and Efficiency in Manufacturing in Brazilian Regions: A Spatial Markov Chain Analysis

This paper analyzes the geography of regional competitiveness in manufacturing in Brazil. The authors estimate stochastic frontiers to calculate regional efficiency of representative firms in 137 regions in the period 2000-2006, in four sectors defined by technological intensity. The efficiency results are analyzed using Markov Spatial Transition Matrices to provide insights into the transition of regions between efficiency levels, considering their local spatial context. The results indicate that geography plays an important role in manufacturing competitiveness. In particular, regions with more competitive neighbors are more likely to improve their relative efficiency (pull effect) over time, and regions with less competitive neighbors are more likely to lose relative efficiency (drag effect). The authors find that the pull effect is stronger than the drag effect.

Waterlogging and fire impacts on nitrogen availability and utilization in a subtropical wet heathland (wallum)

Protein, amino acids and ammonium were the main forms of soluble soil nitrogen in the soil solution of a subtropical heathland (wallum). After fire, soil ammonium and nitrate increased 90- and 60-fold, respectively. Despite this increase in nitrate availability after fire, wallum species exhibited uniformly low nitrate reductase activities and low leaf and xylem nitrate, During waterlogging soil amino acids increased, particularly gamma-aminobutyric acid (GABA) which accounted for over 50% of amino nitrogen. Non-mycorrhizal wallum species were significantly (P < 0.05) N-15-enriched (0.3-4.3 parts per thousand) compared to species with mycorrhizal associations (ericoid-type, ecto-, va-mycorrhizal) which were strongly depleted in N-15 (-6.3 to -1.8 parts per thousand). Lignotubers and roots had delta(15)N signatures similar to that of the leaves of respective species. The exceptions were fine roots of ecto-, ecto/va-, and ericoid type mycorrhizal species which were enriched in N-15 (0.1-2 4 parts per thousand). The delta(15)N signatures of delta(15)N(total soil N) and delta(15)N(soil NH4+) were in the range 3.7-4.5 parts per thousand, whereas delta(15)N(soil NO3-) was significantly (P < 0.05) more enriched in N-15 (9.2-9.8 parts per thousand). It is proposed that there is discrimination against N-15 during transfer of nitrogen from fungal to plant partner. Roots of selected species incorporated nitrogen sources in the order of preference: ammonium > glycine > nitrate. The exception were proteoid roots of Hakea (Proteaceae) which incorporated equal amounts of glycine and ammonium.

Occlusal outcomes and efficiency of 1-and 2-phase protocols in the treatment of Class II Division 1 malocclusion

Introduction: The purpose of this study was to compare the occlusal outcomes and the efficiency of 1-phase and 2-phase treatment protocols in Class II Division 1 malocclusions. Treatment efficiency was defined as a change in the occlusal characteristics in a shorter treatment time. Methods: Class II Division 1 subjects ( n = 139) were divided into 2 groups according to the treatment protocol for Class II correction. Group 1 comprised 78 patients treated with a 1-phase treatment protocol at initial and final mean ages of 12.51 and 14.68 years. Group 2 comprised 61 patients treated with a 2-phase treatment protocol at initial and final mean ages of 11.21 and 14.70 years. Lateral cephalometric radiographs were taken at the pretreatment stage to evaluate morphological differences in the groups. The initial and final study models of the patients were evaluated by using the peer assessment rating index. Chi-square tests were used to test for differences between the 2 groups for categorical variables. Variables regarding occlusal results were compared by using independent t tests. A linear regression analysis was completed, with total treatment time as the dependent variable, to identify clinical factors that predict treatment length for patients with Class II malocclusions. Results: Similar occlusal outcomes were obtained between the 1-phase and the 2-phase treatment protocols, but the duration of treatment was significantly shorter in the 1-phase treatment protocol group. Conclusions: Treatment of Class II Division 1 malocclusions is more efficient with the 1-phase than the 2-phase treatment protocol.

Biogeographical concordance and efficiency of taxon indicators for establishing conservation priority in a tropical rainforest biota

Prioritizing areas for conservation requires the use of surrogates for assessing overall patterns of biodiversity. Effective surrogates will reflect general biogeographical patterns and the evolutionary processes that have given rise to these and their efficiency is likely to lie influenced by several factors, including the spatial scale of species turnover and the overall congruence of the biogeographical history. We examine patterns of surrogacy for insects, snails, one family of plants and vertebrates from rainforests of northeast Queensland, an area characterized by high endemicity and an underlying history of climate-induced vicariance. Nearly all taxa provided some level of prediction of the conservation values For others. However, despite an overall correlation of the patterns of species richness and complementarity, the efficiency of surrogacy was highly asymmetric.. snails and insects were strong predictors of conservation priorities for vertebrates, but not vice versa. These results confirm predictions that taxon surrogates can be effective in highly diverse tropical systems where there is a strong history of vicariant biogeography, but also indicate that correlated patterns for species richness and/or complementarity do not guarantee that one taxon will be efficient as a surrogate for another. In our case, the highly diverse and narrowly distributed invertebrates were more efficient as predictors than the less diverse and more broadly distributed vertebrates.