Reframing reverse logistics, reducing costs

A Work Project, presented as part of the requirements for the Award of a Masters Degree in Management from the NOVA – School of Business and Economics

Rationalization, Kunstwollen and technical means of expressivity. The example of the romantic piano

This article seeks to retrace some of the empirical, historical and sociological elements of Max Weber Sociology of music. Even if he is first and foremost interested in the process of rationalisation throughout western civilisation, his Sociology of music is founded on the idea of the technical medium, which he explores in several different directions. This idea will be examined here by means of several examples drawn from western music, particularly from the romantic piano repertoire.

A note on quasi-stationary distributions of birth-death processes and the SIS logistic epidemic

For Markov processes on the positive integers with the origin as an absorbing state, Ferrari, Kesten, Martinez and Picco studied the existence of quasi-stationary and limiting conditional distributions by characterizing quasi-stationary distributions as fixed points of a transformation Phi on the space of probability distributions on {1, 2,.. }. In the case of a birth-death process, the components of Phi(nu) can be written down explicitly for any given distribution nu. Using this explicit representation, we will show that Phi preserves likelihood ratio ordering between distributions. A conjecture of Kryscio and Lefevre concerning the quasi-stationary distribution of the SIS logistic epidemic follows as a corollary.

Logistic optimization in tourism networks

55th European Regional Science Association Congress, Lisbon, Portugal (25-28 August 2015).

Predicting Xerostomia induced by IMRT treatments: A logistic regression approach

Radiotherapy is one of the main treatments used against cancer. Radiotherapy uses radiation to destroy cancerous cells trying, at the same time, to minimize the damages in healthy tissues. The planning of a radiotherapy treatment is patient dependent, resulting in a lengthy trial and error procedure until a treatment complying as most as possible with the medical prescription is found. Intensity Modulated Radiation Therapy (IMRT) is one technique of radiation treatment that allows the achievement of a high degree of conformity between the area to be treated and the dose absorbed by healthy tissues. Nevertheless, it is still not possible to eliminate completely the potential treatments’ side-effects. In this retrospective study we use the clinical data from patients with head-and-neck cancer treated at the Portuguese Institute of Oncology of Coimbra and explore the possibility of classifying new and untreated patients according to the probability of xerostomia 12 months after the beginning of IMRT treatments by using a logistic regression approach. The results obtained show that the classifier presents a high discriminative ability in predicting the binary response “at risk for xerostomia at 12 months”

Resilience of logistic service providers facing a port strike: a case study

The purpose of this thesis is to study the impact of a port strike on companies that perform as logistic service providers in a supply chain (SC), here denominated 3PL (third-party logistic providers). These companies are highly dependent on ports to perform their activity, since they provide international services. Consequently, a disruption in a port can seriously impair their business. A stevedores’ strike is one of the possible disruptions that can affect ports. This study aims to analyze the negative effects caused by this disruption, and what strategies 3PLs may implement in order to keep their performance levels stable and have a quick recovery time. Within this objective, the first step will be to establish a theoretical context about the maritime port’s sector and 3PLs in a SC context, to then expand the concept of a resilient SC, and finally to develop a theoretical framework in order to better contextualize the case study. Subsequently, the impact of a port strike will be quantified by using a case study comprising three companies, covering the areas of land and sea distribution and port operations. Information from primary sources was assembled in two phases: first via e-mail and, in a second phase, through a personal interview. The information from secondary sources was obtained through television news, internet and conferences, enabling its cross-analysis. Finally, by analyzing the collected data, it will be possible to draw conclusions about the measures carried out by each company to minimize the negative effects of the strike, thus contributing to a more resilient SC. As a conclusion, a stevedores’ strike will create a snow-ball of negative effects in the SC, degrading all relevant KPIs (key performance indicators) of the 3PLs under study. No mitigation and contingency strategies available proved really effective to reduce the negative effects of a port strike disruption.

Methodical Bases of the Integrated Electrotechnical Complexes Life Cycle Logistic Support

Complex aspects of management by life cycle ofelectrotechnical complexes of the oil-extracting enterprises by amethod of the integrated logistic support are considered.

Evaluating sampling strategies and logistic regression methods for modelling complex land cover changes

The role of land cover change as a significant component of global change has become increasingly recognized in recent decades. Large databases measuring land cover change, and the data which can potentially be used to explain the observed changes, are also becoming more commonly available. When developing statistical models to investigate observed changes, it is important to be aware that the chosen sampling strategy and modelling techniques can influence results. We present a comparison of three sampling strategies and two forms of grouped logistic regression models (multinomial and ordinal) in the investigation of patterns of successional change after agricultural land abandonment in Switzerland. Results indicated that both ordinal and nominal transitional change occurs in the landscape and that the use of different sampling regimes and modelling techniques as investigative tools yield different results. Synthesis and applications. Our multimodel inference identified successfully a set of consistently selected indicators of land cover change, which can be used to predict further change, including annual average temperature, the number of already overgrown neighbouring areas of land and distance to historically destructive avalanche sites. This allows for more reliable decision making and planning with respect to landscape management. Although both model approaches gave similar results, ordinal regression yielded more parsimonious models that identified the important predictors of land cover change more efficiently. Thus, this approach is favourable where land cover change pattern can be interpreted as an ordinal process. Otherwise, multinomial logistic regression is a viable alternative.

A logistic regression approach to estimating customer profit loss due to lapses in insurance

This article focuses on business risk management in the insurance industry. A methodology for estimating the profit loss caused by each customer in the portfolio due to policy cancellation is proposed. Using data from a European insurance company, customer behaviour over time is analyzed in order to estimate the probability of policy cancelation and the resulting potential profit loss due to cancellation. Customers may have up to two different lines of business contracts: motor insurance and other diverse insurance (such as, home contents, life or accident insurance). Implications for understanding customer cancellation behaviour as the core of business risk management are outlined.

Binary classification of dyslipidemia from the waist-to-hip ratio and body mass index: a comparison of linear, logistic, and CART models.

BACKGROUND: We sought to improve upon previously published statistical modeling strategies for binary classification of dyslipidemia for general population screening purposes based on the waist-to-hip circumference ratio and body mass index anthropometric measurements. METHODS: Study subjects were participants in WHO-MONICA population-based surveys conducted in two Swiss regions. Outcome variables were based on the total serum cholesterol to high density lipoprotein cholesterol ratio. The other potential predictor variables were gender, age, current cigarette smoking, and hypertension. The models investigated were: (i) linear regression; (ii) logistic classification; (iii) regression trees; (iv) classification trees (iii and iv are collectively known as "CART"). Binary classification performance of the region-specific models was externally validated by classifying the subjects from the other region. RESULTS: Waist-to-hip circumference ratio and body mass index remained modest predictors of dyslipidemia. Correct classification rates for all models were 60-80%, with marked gender differences. Gender-specific models provided only small gains in classification. The external validations provided assurance about the stability of the models. CONCLUSIONS: There were no striking differences between either the algebraic (i, ii) vs. non-algebraic (iii, iv), or the regression (i, iii) vs. classification (ii, iv) modeling approaches. Anticipated advantages of the CART vs. simple additive linear and logistic models were less than expected in this particular application with a relatively small set of predictor variables. CART models may be more useful when considering main effects and interactions between larger sets of predictor variables.

Validation of Logistic Regression Models for Landslide Susceptibility Maps

A wide range of numerical models and tools have been developed over the last decades to support the decision making process in environmental applications, ranging from physical models to a variety of statistically-based methods. In this study, a landslide susceptibility map of a part of Three Gorges Reservoir region of China was produced, employing binary logistic regression analyses. The available information includes the digital elevation model of the region, geological map and different GIS layers including land cover data obtained from satellite imagery. The landslides were observed and documented during the field studies. The validation analysis is exploited to investigate the quality of mapping.

Disfunções orgânicas de pacientes internados em Unidades de Terapia Intensiva segundo o Logistic Organ Dysfunction System

Foi objetivo do estudo verificar as associações entre a probabilidade de morte, número e tipo de insuficiências orgânicas na admissão de pacientes na Unidade de Terapia Intensiva (UTI), segundo o Logistic Organ Dysfunction System (LODS), e as seguintes variáveis: tempo de internação, condição de saída e readmissão na unidade. Estudo prospectivo longitudinal de 600 pacientes adultos internados em UTI gerais de quatro hospitais do Município de São Paulo. Como resultados, a probabilidade de morte apresentou associação com as condições de saída da UTI (p<0,001). Também houve associação do número de insuficiências orgânicas com as condição de saída (p<0,001) e tempo de internação na UTI (p<0,001). Quanto ao tipo de insuficiências e tempo de internação na Unidade houve diferença apenas entre os pacientes com insuficiência neurológica (p<0,001), pulmonar (p<0,001) e renal (p=0,020). A readmissão dos pacientes na UTI não teve associação com nenhuma das variáveis estudadas.

Validation procedures in radiological diagnostic models. Neural network and logistic regression

The objective of this paper is to compare the performance of twopredictive radiological models, logistic regression (LR) and neural network (NN), with five different resampling methods. One hundred and sixty-seven patients with proven calvarial lesions as the only known disease were enrolled. Clinical and CT data were used for LR and NN models. Both models were developed with cross validation, leave-one-out and three different bootstrap algorithms. The final results of each model were compared with error rate and the area under receiver operating characteristic curves (Az). The neural network obtained statistically higher Az than LR with cross validation. The remaining resampling validation methods did not reveal statistically significant differences between LR and NN rules. The neural network classifier performs better than the one based on logistic regression. This advantage is well detected by three-fold cross-validation, but remains unnoticed when leave-one-out or bootstrap algorithms are used.