An interaction and network perspective of horizontal relationships in the portuguese pharmaceutical industry

Doutoramento em Gestão

Energy consumption and energy efficiency in olive oil mills: case studies in Portugal and Spain in the frame of TESLA project

TESLA project (Transfering Energy Save Laid on Agroindustry) financed by the European Commission, had the main goals of evaluating the energy consumption and to identify the best available practices to improve energy efficiency in key agro-food sectors, such as the olive oil mills. A general analysis of energy consumptions allowed identifying the partition between electrical and thermal energy (approximately 50%) and the production processes responsible for the higher energy consumptions, as being the in the mill and paste preparation and the phases separation. Some measures for reducing energy waste and for improving energy efficiency were identified and the impact was evaluated by using the TESLA tool developed by Circe and available at the TESLA website.

Characterisation of the sewage microbiome in four European cities throughout the COVID-19 pandemic by means of ecological and network modelling

The purpose of this work was to investigate possible patterns occurring in the sewage bacterial content of four cities (Bologna, Budapest, Rome, Rotterdam) over time (March 2020 - November 2021), also considering the possible effects of the lockdown periods due to the COVID-19 pandemic. The sewage metagenomics data were provided within VEO (Versatile Emerging infectious disease Observatory) project. The first analysis was the evaluation of the between samples diversity, looking for (dis)similarities among the cities, as well as among different time periods (seasonality). To this aim, we computed both similarity networks and Principal Coordinate Analysis (PCoA) plots based on the Bray-Curtis metric. Then, the alpha-biodiversity of the samples was estimated by means of different diversity indices. By looking at the temporal behaviour of the biodiversity in the four cities, we noticed an abrupt decrease in both Rome and Budapest in the Summer of 2020, that is related to: the prevalence of some species when the minimum occurred, and the change in correlations among species (studied via correlation networks), which is enriched in the period of minimum biodiversity. Rotterdam samples seem to be very different with respect to those from the other cities, as confirmed by PCoA. Moreover, the Rotterdam time series is proved to be stable and stationary also in terms of biodiversity. The low variability in the Rotterdam samples seems to be related to the species of Pseudomonas genus, which are highly variable and plentiful in the other cities, but are not among the most abundant in Rotterdam. Also, we observed that no seasonality effect emerged from the time series of the four cities. Regarding the impact of lockdown periods due to the COVID-19 pandemic, from the limited data available no effect on the time series considered emerges. More samples will be soon available and these analyses will be performed also on them, so that the possible effects of lockdowns may be studied.

Desempenho operacional da colheita mecanizada de cana-de-açúcar (saccharum spp.) em função da velocidade de deslocamento e rotação do motor da colhedora

Pós-graduação em Agronomia (Energia na Agricultura) - FCA

Restricting the flexibility in DEA models

DEA models have been applied as the benchmarking tool in operations management to empirically account operational and productive efficiency. The wide flexibility in assigning the weights in DEA approach can result on indicators of efficiency who do not take account the relative importance of some inputs. In order to overcome this limitation, in this research we apply the DEA model under restricted weight specification. This model is applied to Spanish hotel companies in order to measure operational efficiency. The restricted weight specification enables us to decrease the influence of assigning unrealistic weights in some units and improve the efficiency estimation and to increase the discriminating potential of the conventional DEA model.

Value added logistics in supply and demand chains. Smile. Part 1. eBusiness between global company and itslocal sme supplier network

VALOSADE (Value Added Logistics in Supply and Demand Chains) is the research project of Anita Lukka's VALORE (Value Added Logistics Research) research team inLappeenranta University of Technology. VALOSADE is included in ELO (Ebusiness logistics) technology program of Tekes (Finnish Technology Agency). SMILE (SME-sector, Internet applications and Logistical Efficiency) is one of four subprojects of VALOSADE. SMILE research focuses on case network that is composed of small and medium sized mechanical maintenance service providers and global wood processing customers. Basic principle of SMILE study is communication and ebusiness insupply and demand network. This first phase of research concentrates on creating backgrounds for SMILE study and for ebusiness solutions of maintenance case network. The focus is on general trends of ebusiness in supply chains and networksof different industries; total ebusiness system architecture of company networks; ebusiness strategy of company network; information value chain; different factors, which influence on ebusiness solution of company network; and the correlation between ebusiness and competitive advantage. Literature, interviews and benchmarking were used as research methods in this qualitative case study. Networks and end-to-end supply chains are the organizational structures, which can add value for end customer. Information is one of the key factors in these decentralized structures. Because of decentralization of business, information is produced and used in different companies and in different information systems. Information refinement services are needed to manage information flows in company networksbetween different systems. Furthermore, some new solutions like network information systems are utilised in optimising network performance and in standardizingnetwork common processes. Some cases have however indicated, that utilization of ebusiness in decentralized business model is not always a necessity, but value-add of ICT must be defined case-specifically. In the theory part of report, different ebusiness and architecture models are introduced. These models are compared to empirical case data in research results. The biggest difference between theory and empirical data is that models are mainly developed for large-scale companies - not for SMEs. This is due to that implemented network ebusiness solutions are mainly large company centered. Genuine SME network centred ebusiness models are quite rare, and the study in that area has been few in number. Business relationships between customer and their SME suppliers are nowadays concentrated more on collaborative tactical and strategic initiatives besides transaction based operational initiatives. However, ebusiness systems are further mainly based on exchange of operational transactional data. Collaborative ebusiness solutions are in planning or pilot phase in most case companies. Furthermore, many ebusiness solutions are nowadays between two participants, but network and end-to-end supply chain transparency and information systems are quite rare. Transaction volumes, data formats, the types of exchanged information, information criticality,type and duration of business relationship, internal information systems of partners, processes and operation models (e.g. different ordering models) differ among network companies, and furthermore companies are at different stages on networking and ebusiness readiness. Because of former factors, different customer-supplier combinations in network must utilise totally different ebusiness architectures, technologies, systems and standards.

Orchestration of energy efficiency capabilities for a sustainable network management

The energy demand for operating Information and Communication Technology (ICT) systems has been growing, implying in high operational costs and consequent increase of carbon emissions. Both in datacenters and telecom infrastructures, the networks represent a significant amount of energy spending. Given that, there is an increased demand for energy eficiency solutions, and several capabilities to save energy have been proposed. However, it is very dificult to orchestrate such energy eficiency capabilities, i.e., coordinate or combine them in the same network, ensuring a conflict-free operation and choosing the best one for a given scenario, ensuring that a capability not suited to the current bandwidth utilization will not be applied and lead to congestion or packet loss. Also, there is no way in the literature to do this taking business directives into account. In this regard, a method able to orchestrate diferent energy eficiency capabilities is proposed considering the possible combinations and conflicts among them, as well as the best option for a given bandwidth utilization and network characteristics. In the proposed method, the business policies specified in a high-level interface are refined down to the network level in order to bring highlevel directives into the operation, and a Utility Function is used to combine energy eficiency and performance requirements. A Decision Tree able to determine what to do in each scenario is deployed in a Software Defined Network environment. The proposed method was validated with diferent experiments, testing the Utility Function, checking the extra savings when combining several capabilities, the decision tree interpolation and dynamicity aspects. The orchestration proved to be valid to solve the problem of finding the best combination for a given scenario, achieving additional savings due to the combination, besides ensuring a conflict-free operation.

Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector

Guest editorial Ali Emrouznejad is a Senior Lecturer at the Aston Business School in Birmingham, UK. His areas of research interest include performance measurement and management, efficiency and productivity analysis as well as data mining. He has published widely in various international journals. He is an Associate Editor of IMA Journal of Management Mathematics and Guest Editor to several special issues of journals including Journal of Operational Research Society, Annals of Operations Research, Journal of Medical Systems, and International Journal of Energy Management Sector. He is in the editorial board of several international journals and co-founder of Performance Improvement Management Software. William Ho is a Senior Lecturer at the Aston University Business School. Before joining Aston in 2005, he had worked as a Research Associate in the Department of Industrial and Systems Engineering at the Hong Kong Polytechnic University. His research interests include supply chain management, production and operations management, and operations research. He has published extensively in various international journals like Computers & Operations Research, Engineering Applications of Artificial Intelligence, European Journal of Operational Research, Expert Systems with Applications, International Journal of Production Economics, International Journal of Production Research, Supply Chain Management: An International Journal, and so on. His first authored book was published in 2006. He is an Editorial Board member of the International Journal of Advanced Manufacturing Technology and an Associate Editor of the OR Insight Journal. Currently, he is a Scholar of the Advanced Institute of Management Research. Uses of frontier efficiency methodologies and multi-criteria decision making for performance measurement in the energy sector This special issue aims to focus on holistic, applied research on performance measurement in energy sector management and for publication of relevant applied research to bridge the gap between industry and academia. After a rigorous refereeing process, seven papers were included in this special issue. The volume opens with five data envelopment analysis (DEA)-based papers. Wu et al. apply the DEA-based Malmquist index to evaluate the changes in relative efficiency and the total factor productivity of coal-fired electricity generation of 30 Chinese administrative regions from 1999 to 2007. Factors considered in the model include fuel consumption, labor, capital, sulphur dioxide emissions, and electricity generated. The authors reveal that the east provinces were relatively and technically more efficient, whereas the west provinces had the highest growth rate in the period studied. Ioannis E. Tsolas applies the DEA approach to assess the performance of Greek fossil fuel-fired power stations taking undesirable outputs into consideration, such as carbon dioxide and sulphur dioxide emissions. In addition, the bootstrapping approach is deployed to address the uncertainty surrounding DEA point estimates, and provide bias-corrected estimations and confidence intervals for the point estimates. The author revealed from the sample that the non-lignite-fired stations are on an average more efficient than the lignite-fired stations. Maethee Mekaroonreung and Andrew L. Johnson compare the relative performance of three DEA-based measures, which estimate production frontiers and evaluate the relative efficiency of 113 US petroleum refineries while considering undesirable outputs. Three inputs (capital, energy consumption, and crude oil consumption), two desirable outputs (gasoline and distillate generation), and an undesirable output (toxic release) are considered in the DEA models. The authors discover that refineries in the Rocky Mountain region performed the best, and about 60 percent of oil refineries in the sample could improve their efficiencies further. H. Omrani, A. Azadeh, S. F. Ghaderi, and S. Abdollahzadeh presented an integrated approach, combining DEA, corrected ordinary least squares (COLS), and principal component analysis (PCA) methods, to calculate the relative efficiency scores of 26 Iranian electricity distribution units from 2003 to 2006. Specifically, both DEA and COLS are used to check three internal consistency conditions, whereas PCA is used to verify and validate the final ranking results of either DEA (consistency) or DEA-COLS (non-consistency). Three inputs (network length, transformer capacity, and number of employees) and two outputs (number of customers and total electricity sales) are considered in the model. Virendra Ajodhia applied three DEA-based models to evaluate the relative performance of 20 electricity distribution firms from the UK and the Netherlands. The first model is a traditional DEA model for analyzing cost-only efficiency. The second model includes (inverse) quality by modelling total customer minutes lost as an input data. The third model is based on the idea of using total social costs, including the firm’s private costs and the interruption costs incurred by consumers, as an input. Both energy-delivered and number of consumers are treated as the outputs in the models. After five DEA papers, Stelios Grafakos, Alexandros Flamos, Vlasis Oikonomou, and D. Zevgolis presented a multiple criteria analysis weighting approach to evaluate the energy and climate policy. The proposed approach is akin to the analytic hierarchy process, which consists of pairwise comparisons, consistency verification, and criteria prioritization. In the approach, stakeholders and experts in the energy policy field are incorporated in the evaluation process by providing an interactive mean with verbal, numerical, and visual representation of their preferences. A total of 14 evaluation criteria were considered and classified into four objectives, such as climate change mitigation, energy effectiveness, socioeconomic, and competitiveness and technology. Finally, Borge Hess applied the stochastic frontier analysis approach to analyze the impact of various business strategies, including acquisition, holding structures, and joint ventures, on a firm’s efficiency within a sample of 47 natural gas transmission pipelines in the USA from 1996 to 2005. The author finds that there were no significant changes in the firm’s efficiency by an acquisition, and there is a weak evidence for efficiency improvements caused by the new shareholder. Besides, the author discovers that parent companies appear not to influence a subsidiary’s efficiency positively. In addition, the analysis shows a negative impact of a joint venture on technical efficiency of the pipeline company. To conclude, we are grateful to all the authors for their contribution, and all the reviewers for their constructive comments, which made this special issue possible. We hope that this issue would contribute significantly to performance improvement of the energy sector.

Physical-chemical and operational performance of an anaerobic baffled reactor (ABR) treating swine wastewater

Since hog raising concentrates a huge amount of swine manure in small areas, it is considered by the environmental government organizations to be one of the most potentially pollutant activities. Therefore the main objective of this research was to evaluate by operational criteria and removal efficiency, the performance of a Anaerobic Baffled Reactor (ABR), working as a biological pre-treatment of swine culture effluents. The physical-chemical analyses carried out were: total COD, BOD(5), total solids (TS), fix (TFS) and volatiles (TVS), temperature, pH, total Kjeldahl nitrogen, phosphorus, total acidity and alkalinity. The ABR unit worked with an average efficiency of 65.2 and 76.2%, respectively, concerning total COD and BOD(5), with a hydraulic retention time (HRT) about 15 hours. The results for volumetric organic loading rate (VOLR), organic loading rate (OLR) and hydraulic loading rate (HLR) were: 4.46 kg BOD m(-3) day(-1); 1.81 kg BOD(5) kg TVS(-1) day(-1) and 1.57 m(3) m(-3) day(-1), respectively. The average efficiency of the whole treatment system for total COD and BOD(5) removal were 66.5 and 77.8%, showing an adequate performance in removing die organic matter from swine wastewater.

Multiple Linear Regression and Artificial Neural Networks to Predict Time and Efficiency of Soil Vapor Extraction

The prediction of the time and the efficiency of the remediation of contaminated soils using soil vapor extraction remain a difficult challenge to the scientific community and consultants. This work reports the development of multiple linear regression and artificial neural network models to predict the remediation time and efficiency of soil vapor extractions performed in soils contaminated separately with benzene, toluene, ethylbenzene, xylene, trichloroethylene, and perchloroethylene. The results demonstrated that the artificial neural network approach presents better performances when compared with multiple linear regression models. The artificial neural network model allowed an accurate prediction of remediation time and efficiency based on only soil and pollutants characteristics, and consequently allowing a simple and quick previous evaluation of the process viability.

Airport Congestion and Airline Network Structure

This paper provides a theoretical and empirical analysis of the relationship between airport congestion and airline network structure. We find that the development of hub-and-spoke (HS) networks may have detrimental effects on social welfare in presence of airport congestion. The theoretical analysis shows that, although airline pro ts are typically higher under HS networks, congestion could create incentives for airlines to adopt fully-connected (FC) networks. However, the welfare analysis leads to the conclusion that airlines may have an inefficient bias towards HS networks. In line with the theoretical analysis, our empirical results show that network airlines are weakly infl uenced by congestion in their choice of frequencies from/to their hub airports. Consistently with this result, we con firm that delays are higher in hub airports controlling for concentration and airport size. Keywords: airlines; airport congestion; fully-connected networks, hub-and-spoke net- works; network efficiency JEL Classifi cation Numbers: L13; L2; L93

Natural resource windfalls and efficiency of local government expenditures: evidence from Peru

We study the role of natural resource windfalls in explaining the efficiency of public expenditures. Using a rich dataset of expenditures and public good provision for 1,836 municipalities in Peru for period 2001-2010, we estimate a non-monotonic relationship between the efficiency of public good provision and the level of natural resource transfers. Local governments that were extremely favored by the boom of mineral prices were more efficient in using fiscal windfalls whereas those benefited with modest transfers were more inefficient. These results can be explained by the increase in political competition associated with the boom. However, the fact that increases in efficiency were related to reductions in public good provision casts doubts about the beneficial effects of political competition in promoting efficiency.

Observing wind, aerosol particles, clouds and precipitation: Finland's new ground-based remote-sensing network

The Finnish Meteorological Institute, in collaboration with the University of Helsinki, has established a new ground-based remote-sensing network in Finland. The network consists of five topographically, ecologically and climatically different sites distributed from southern to northern Finland. The main goal of the network is to monitor air pollution and boundary layer properties in near real time, with a Doppler lidar and ceilometer at each site. In addition to these operational tasks, two sites are members of the Aerosols, Clouds and Trace gases Research InfraStructure Network (ACTRIS); a Ka band cloud radar at Sodankylä will provide cloud retrievals within CloudNet, and a multi-wavelength Raman lidar, PollyXT (POrtabLe Lidar sYstem eXTended), in Kuopio provides optical and microphysical aerosol properties through EARLINET (the European Aerosol Research Lidar Network). Three C-band weather radars are located in the Helsinki metropolitan area and are deployed for operational and research applications. We performed two inter-comparison campaigns to investigate the Doppler lidar performance, compare the backscatter signal and wind profiles, and to optimize the lidar sensitivity through adjusting the telescope focus length and data-integration time to ensure sufficient signal-to-noise ratio (SNR) in low-aerosol-content environments. In terms of statistical characterization, the wind-profile comparison showed good agreement between different lidars. Initially, there was a discrepancy in the SNR and attenuated backscatter coefficient profiles which arose from an incorrectly reported telescope focus setting from one instrument, together with the need to calibrate. After diagnosing the true telescope focus length, calculating a new attenuated backscatter coefficient profile with the new telescope function and taking into account calibration, the resulting attenuated backscatter profiles all showed good agreement with each other. It was thought that harsh Finnish winters could pose problems, but, due to the built-in heating systems, low ambient temperatures had no, or only a minor, impact on the lidar operation – including scanning-head motion. However, accumulation of snow and ice on the lens has been observed, which can lead to the formation of a water/ice layer thus attenuating the signal inconsistently. Thus, care must be taken to ensure continuous snow removal.

Integrated Intermediate Waveband and Wavelength Switching for Optical WDM Mesh Networks

As wavelength-division multiplexing (WDM) evolves towards practical applications in optical transport networks, waveband switching (WBS) has been introduced to cut down the operational costs and to reduce the complexities and sizes of network components, e.g., optical cross-connects (OXCs). This paper considers the routing, wavelength assignment and waveband assignment (RWWBA) problem in a WDM network supporting mixed waveband and wavelength switching. First, the techniques supporting waveband switching are studied, where a node architecture enabling mixed waveband and wavelength switching is proposed. Second, to solve the RWWBA problem with reduced switching costs and improved network throughput, the cost savings and call blocking probabilities along intermediate waveband-routes are analyzed. Our analysis reveals some important insights about the cost savings and call blocking probability in relation to the fiber capacity, the candidate path, and the traffic load. Third, based on our analysis, an online integrated intermediate WBS algorithm (IIWBS) is proposed. IIWBS determines the waveband switching route for a call along its candidate path according to the node connectivity, the link utilization, and the path length information. In addition, the IIWBS algorithm is adaptive to real network applications under dynamic traffic requests. Finally, our simulation results show that IIWBS outperforms a previous intermediate WBS algorithm and RWA algorithms in terms of network throughput and cost efficiency.

Collaborative Change: Environmental Jolt, Network (Re)Design and Firm Performance

Motivated by the need to understand which are the underlying forces that trigger network evolution, we develop a multilevel theoretical and empirically testable model to examine the relationship between changes in the external environment and network change. We refer to network change as the dissolution or replacement of an interorganizational tie, adding also the case of the formation of new ties with new or preexisting partners. Previous research has paid scant attention to the organizational consequences of quantum change enveloping entire industries in favor of an emphasis on continuous change. To highlight radical change we introduce the concept of environmental jolt. The September 11 terrorist attacks provide us with a natural experiment to test our hypotheses on the antecedents and the consequences of network change. Since network change can be explained at multiple levels, we incorporate firm-level variables as moderators. The empirical setting is the global airline industry, which can be regarded as a constantly changing network of alliances. The study reveals that firms react to environmental jolts by forming homophilous ties and transitive triads as opposed to the non jolt periods. Moreover, we find that, all else being equal, firms that adopt a brokerage posture will have positive returns. However, we find that in the face of an environmental jolt brokerage relates negatively to firm performance. Furthermore, we find that the negative relationship between brokerage and performance during an environmental jolt is more significant for larger firms. Our findings suggest that jolts are an important predictor of network change, that they significantly affect operational returns and should be thus incorporated in studies of network dynamics.