Monikanavaisuuden hyödyt ja haitat - tutkimus monikanavaisuudesta palveluntarjoajan ja asiakkaan näkökulmasta

Tämän tutkimuksen tavoitteena oli selvittää, voidaanko asiakkaan ja palveluntarjoajan odotukset yhdistää muodostettaessa palveluntarjoajan monikanavamallia. Monikanavaisuus tuo asiakkaalle mahdollisuuksia ajasta ja paikasta riippumattomaan asiointiin. Asiakkaan näkökulmasta tämä tarkoittaa usein sitä, että hänen oppimansa asiointitapa muuttuu. Asiakas kokee haittana sen, että joutuu panostamaan uuden asiointitavan opettelemiseen ja odottaa tämän muutoksen tuovan hänelle hyötyjä. Monikanavaisuuden hyödyt asiakkaalle punnitaan tässä muutostilanteessa. Palveluntarjoaja odottaa monikanavamallin tuovan kustannussäästöjä, sillä kanavavalinnat ovat keino kehittää asiakkuuksia ja vaikuttaa yrityksen kannattavuuteen pitkällä aikajänteellä. Monikanavamallin toteuttaminen vaatii palveluntarjoajalta alkuvaiheessa resursseja, investointeja ja halutun muutoksen tavoitteellista johtamista. Tutkittavat asiakkaat valittiin Suomen Posti Oyj:n Yritykset ja yritykset –asiakassegmentistä. Tutkimuksessa ei löytynyt asiakaskohtaisia eroja asiakkaiden odotuksista palveluntarjoajien monikanavamalleihin, mutta hyötyodotusten suhteen tunnistettiin kolme erilaista asiakastyyppiä: kustannussäästöjä odottavat hintaorientoituneet asiakkaat, palvelun entistä parempaa sujumista odottavat palveluorientoituneet asiakkaat ja oman valinnanvapautensa merkitystä painottavat asiakassuhdeorientoituneet asiakkaat. Palveluntarjoajan tulee pystyä viestimään ja argumentoimaan asiointitavan muutoksesta kullekin asiakkaalle merkityksellisellä tavalla. Teorian ja empirian pohjalta voidaan sanoa, että asiakkaan ja palveluntarjoajan odotukset voidaan yhdistää muodostettaessa palveluntarjoajan monikanavamallia. Tämä edellyttää, että palveluntarjoaja tuntee asiakkaansa niin hyvin, että tietää millaiset eri asiakkaiden hyötyodotukset ovat.

Risk-Return Trade-Off for European Stock Markets

This paper adopts dynamic factor models with macro-finance predictors to test the intertemporal risk-return relation for 13 European stock markets. We identify country specific, euro area, and global macro-finance factors to determine the conditional risk and return. Empirically, the risk- return trade-off is generally negative. However, a Markov switching model documents that there is time-variation in this trade-off that is linked to the state of the economy. Keywords: Risk-return trade-off; Dynamic factor model; Macro-finance predictors; European stock markets; Markov switching model JEL Classifications: C22; G11; G12; G17

An experimental and theoretical study of multiphase flow in a circulating fluidized bed

A systematic averaging procedure has been derived in order to obtain an integral form of conservation equations for dispersed multiphase flow, especially applicable to fluidized beds. A similar averaging method is applied further to formulate macroscopic integral equations, which can be used in one-dimensional and macroscopic multi dimensional models. Circulating fluid bed hydrodynamics has been studied experimentally and both macroscopic and microscopic flow profiles have been measured in a cold model. As an application of the theory, the one dimensional model has been used to study mass and momentum conservation of gas and solid in a circulating fluid bed. Axial solid mixing has also been modelled by the one dimensional model and mixing parameters have been evaluated.

Influence of process parameters on the color and texture of passion fruit albedo preserved in syrup

The industrialization of passion fruit in the form of juice produces considerable amounts of residue that could be used as food. The objective of the present study was to determine the effects of the volume of passion fruit juice added to the syrup and the cooking time on the color and texture of passion fruit albedo preserved in syrup. Multi-linear models were well fit to describe the value for a* (for the albedo) the values for b* (for the albedo and syrup), which exhibited high correlation coefficients of 98%, 84%, and 88%, respectively. The volume of passion fruit juice added and the cooking time of the albedos in the syrup, involved in the processing of passion fruit albedo preserves in syrup, significantly affected color analyses. The texture was not affected by the parameters studied. Therefore, the use of larger volumes of passion fruit juice and longer cooking time is recommended for the production of passion fruit albedo preserves in syrup to achieve the characteristic yellow color of the fruit.

Passive Solar Building Design Using Genetic Programming

Passive solar building design is the process of designing a building while considering sunlight exposure for receiving heat in winter and rejecting heat in summer. The main goal of a passive solar building design is to remove or reduce the need of mechanical and electrical systems for cooling and heating, and therefore saving energy costs and reducing environmental impact. This research will use evolutionary computation to design passive solar buildings. Evolutionary design is used in many research projects to build 3D models for structures automatically. In this research, we use a mixture of split grammar and string-rewriting for generating new 3D structures. To evaluate energy costs, the EnergyPlus system is used. This is a comprehensive building energy simulation system, which will be used alongside the genetic programming system. In addition, genetic programming will also consider other design and geometry characteristics of the building as search objectives, for example, window placement, building shape, size, and complexity. In passive solar designs, reducing energy that is needed for cooling and heating are two objectives of interest. Experiments show that smaller buildings with no windows and skylights are the most energy efficient models. Window heat gain is another objective used to encourage models to have windows. In addition, window and volume based objectives are tried. To examine the impact of environment on designs, experiments are run on five different geographic locations. Also, both single floor models and multi-floor models are examined in this research. According to the experiments, solutions from the experiments were consistent with respect to materials, sizes, and appearance, and satisfied problem constraints in all instances.

Testing for a Unit Root in Panels with Dynamic Factors

This paper studies testing for a unit root for large n and T panels in which the cross-sectional units are correlated. To model this cross-sectional correlation, we assume that the data is generated by an unknown number of unobservable common factors. We propose unit root tests in this environment and derive their (Gaussian) asymptotic distribution under the null hypothesis of a unit root and local alternatives. We show that these tests have significant asymptotic power when the model has no incidental trends. However, when there are incidental trends in the model and it is necessary to remove heterogeneous deterministic components, we show that these tests have no power against the same local alternatives. Through Monte Carlo simulations, we provide evidence on the finite sample properties of these new tests.

Sectoral Price Rigidity and Aggregate Dynamics

In this paper, we study the macroeconomic implications of sectoral heterogeneity and, in particular, heterogeneity in price setting, through the lens of a highly disaggregated multi-sector model. The model incorporates several realistic features and is estimated using a mix of aggregate and sectoral U.S. data. The frequencies of price changes implied by our estimates are remarkably consistent with those reported in micro-based studies, especially for non-sale prices. The model is used to study (i) the contribution of sectoral characteristics to the observed cross sectional heterogeneity in sectoral output and inflation responses to a monetary policy shock, (ii) the implications of sectoral price rigidity for aggregate output and inflation dynamics and for cost pass-through, and (iii) the role of sectoral shocks in explaining sectoral prices and quantities.

Genes involved in the metabolism of fatty acids and risk for Crohn's disease in children: a candidate gene study

Contexte - La prévalence de la maladie de Crohn (MC), une maladie inflammatoire chronique du tube digestif, chez les enfants canadiens se situe parmi les plus élevées au monde. Les interactions entre les réponses immunes innées et acquises aux microbes de l'hôte pourraient être à la base de la transition de l’inflammation physiologique à une inflammation pathologique. Le leucotriène B4 (LTB4) est un modulateur clé de l'inflammation et a été associé à la MC. Nous avons postulé que les principaux gènes impliqués dans la voie métabolique du LTB4 pourrait conférer une susceptibilité accrue à l'apparition précoce de la MC. Dans cette étude, nous avons exploré les associations potentielles entre les variantes de l'ADN des gènes ALOX5 et CYP4F2 et la survenue précoce de la MC. Nous avons également examiné si les gènes sélectionnés montraient des effets parent-d'origine, influençaient les phénotypes cliniques de la MC et s'il existait des interactions gène-gène qui modifieraient la susceptibilité à développer la MC chez l’enfant. Méthodes – Dans le cadre d’une étude de cas-parents et de cas-témoins, des cas confirmés, leurs parents et des contrôles ont été recrutés à partir de trois cliniques de gastro-entérologie à travers le Canada. Les associations entre les polymorphismes de remplacement d'un nucléotide simple (SNP) dans les gènes CYP4F2 et ALOX5 ont été examinées. Les associations allélique et génotypiques ont été examinées à partir d’une analyse du génotype conditionnel à la parenté (CPG) pour le résultats cas-parents et à l’aide de table de contingence et de régression logistique pour les données de cas-contrôles. Les interactions gène-gène ont été explorées à l'aide de méthodes de réduction multi-factorielles de dimensionnalité (MDR). Résultats – L’étude de cas-parents a été menée sur 160 trios. L’analyse CPG pour 14 tag-SNP (10 dans la CYP4F2 et 4 dans le gène ALOX5) a révélé la présence d’associations alléliques ou génotypique significatives entre 3 tag-SNP dans le gène CYP4F2 (rs1272, p = 0,04, rs3093158, p = 0.00003, et rs3093145, p = 0,02). Aucune association avec les SNPs de ALOX5 n’a pu être démontrée. L’analyse de l’haplotype de CYP4F2 a montré d'importantes associations avec la MC (test omnibus p = 0,035). Deux haplotypes (GAGTTCGTAA, p = 0,05; GGCCTCGTCG, p = 0,001) montraient des signes d'association avec la MC. Aucun effet parent-d'origine n’a été observé. Les tentatives de réplication pour trois SNPs du gene CYP4F2 dans l'étude cas-témoins comportant 225 cas de MC et 330 contrôles suggèrent l’association dans un de ceux-ci (rs3093158, valeur non-corrigée de p du test unilatéral = 0,03 ; valeur corrigée de p = 0.09). La combinaison des ces deux études a révélé des interactions significatives entre les gènes CYP4F2, ALOX et NOD2. Nous n’avons pu mettre en évidence aucune interaction gène-sexe, de même qu’aucun gène associé aux phénotypes cliniques de la MC n’a pu être identifié. Conclusions - Notre étude suggère que la CYP4F2, un membre clé de la voie métabolique LTB4 est un gène candidat potentiel pour MC. Nous avons également pu mettre en évidence que les interactions entre les gènes de l'immunité adaptative (CYP4F2 et ALOX5) et les gènes de l'immunité innée (NOD2) modifient les risques de MC chez les enfants. D'autres études sur des cohortes plus importantes sont nécessaires pour confirmer ces conclusions.

Apprentissage de représentations musicales à l'aide d'architectures profondes et multiéchelles

L'apprentissage machine (AM) est un outil important dans le domaine de la recherche d'information musicale (Music Information Retrieval ou MIR). De nombreuses tâches de MIR peuvent être résolues en entraînant un classifieur sur un ensemble de caractéristiques. Pour les tâches de MIR se basant sur l'audio musical, il est possible d'extraire de l'audio les caractéristiques pertinentes à l'aide de méthodes traitement de signal. Toutefois, certains aspects musicaux sont difficiles à extraire à l'aide de simples heuristiques. Afin d'obtenir des caractéristiques plus riches, il est possible d'utiliser l'AM pour apprendre une représentation musicale à partir de l'audio. Ces caractéristiques apprises permettent souvent d'améliorer la performance sur une tâche de MIR donnée. Afin d'apprendre des représentations musicales intéressantes, il est important de considérer les aspects particuliers à l'audio musical dans la conception des modèles d'apprentissage. Vu la structure temporelle et spectrale de l'audio musical, les représentations profondes et multiéchelles sont particulièrement bien conçues pour représenter la musique. Cette thèse porte sur l'apprentissage de représentations de l'audio musical. Des modèles profonds et multiéchelles améliorant l'état de l'art pour des tâches telles que la reconnaissance d'instrument, la reconnaissance de genre et l'étiquetage automatique y sont présentés.

Risk Aversion in Inventory Management

Traditional inventory models focus on risk-neutral decision makers, i.e., characterizing replenishment strategies that maximize expected total profit, or equivalently, minimize expected total cost over a planning horizon. In this paper, we propose a framework for incorporating risk aversion in multi-period inventory models as well as multi-period models that coordinate inventory and pricing strategies. In each case, we characterize the optimal policy for various measures of risk that have been commonly used in the finance literature. In particular, we show that the structure of the optimal policy for a decision maker with exponential utility functions is almost identical to the structure of the optimal risk-neutral inventory (and pricing) policies. Computational results demonstrate the importance of this approach not only to risk-averse decision makers, but also to risk-neutral decision makers with limited information on the demand distribution.

Nova Talenta: 2014-2015

Contenido Introducción 1. Inteligencia emocional, liderazgo transformacional y género: factores que influencian el desempeño organizacional / Ana María Galindo Londoño, Sara Urrego Mayorga; Director: Juan Carlos Espinosa Méndez. 2. El rol de la mujer en el liderazgo / Andrea Patricia Cuestas Díaz; Directora: Francoise Venezia Contreras Torres. 3. Liderazgo transformacional, clima organizacional, satisfacción laboral y desempeño. Una revisión de la literatura / Juliana Restrepo Orozco, Ángela Marcela Ochoa Rodríguez; Directora: Françoise Venezia Contreras Torres. 4. “E-Leadership” una perspectiva al mundo de las compañías globalizadas / Ángela Beatriz Morales Morales, Mónica Natalia Aguilera Velandia; Director: Juan Carlos Espinosa. 5. Liderazgo y cultura. Una revisión / Daniel Alejandro Romero Galindo; Directora: Francoise Venezia Contreras Torres. 6. La investigación sobre la naturaleza del trabajo directivo: una revisión de la literatura / Julián Felipe Rodríguez Rivera, María Isabel Álvarez Rodríguez; Director: Juan Javier Saavedra Mayorga. 7. La mujer en la alta dirección en el contexto colombiano / Ana María Moreno, Juliana Moreno Jaramillo ; Directora: Françoise Venezia Contreras Torres. 8. Influencia de la personalidad en el discurso y liderazgo de George W. Bush después del 11 de septiembre de 2011 / Karen Eliana Mesa Torres; Director: Juan Carlos Espinosa. 9. La investigación sobre el campo del followership: una revisión de la literatura / Christian D. Báez Millán, Leidy J. Pinzón Porras; Director: Juan Javier Saavedra Mayorga. 10. El liderazgo desde la perspectiva del poder y la influencia. Una revisión de la literatura / Lina María García, Juan Sebastián Naranjo; Director: Juan Javier Saavedra Mayorga. 11. El trabajo directivo para líderes y gerentes: una visión integradora de los roles organizacionales / Lina Marcela Escobar Campos, Daniel Mora Barrero; Director: Rafael Piñeros. 12. Participación emocional en la toma de decisiones / Lina Rocío Poveda C., Gloria Johanna Rueda L.; Directora: Francoise Contreras T. 13. Estrés y su relación con el liderazgo / María Camila García Sierra, Diana Paola Rocha Cárdenas; Director: Juan Carlos Espinosa. 14. “Burnout y engagement” / María Paola Jaramillo Barrios, Natalia Rojas Mancipe; Director: Rafael Piñeros.

Estimating and Forecasting the Term Structure of Interest Rates:US and Colombia Analysis

In this paper we use the most representative models that exist in the literature on term structure of interest rates. In particular, we explore affine one factor models and polynomial-type approximations such as Nelson and Siegel. Our empirical application considers monthly data of USA and Colombia for estimation and forecasting. We find that affine models do not provide adequate performance either in-sample or out-of-sample. On the contrary, parsimonious models such as Nelson and Siegel have adequate results in-sample, however out-of-sample they are not able to systematically improve upon random walk base forecast.

The turnover of organic carbon in subsoils. Part 2. Modelling carbon turnover

A new model, RothPC-1, is described for the turnover of organic C in the top metre of soil. RothPC-1 is a version of RothC-26.3, an earlier model for the turnover of C in topsoils. In RothPC-1 two extra parameters are used to model turnover in the top metre of soil: one, p, which moves organic C down the profile by an advective process, and the other, s, which slows decomposition with depth. RothPC-1 is parameterized and tested using measurements (described in Part 1, this issue) of total organic C and radiocarbon on soil profiles from the Rothamsted long-term field experiments, collected over a period of more than 100 years. RothPC-1 gives fits to measurements of organic C and radiocarbon in the 0-23, 23-46, 46-69 and 69-92 cm layers of soil that are almost all within (or close to) measurement error in two areas of regenerating woodland (Geescroft and Broadbalk Wildernesses) and an area of cultivated land from the Broadbalk Continuous Wheat Experiment. The fits to old grassland (the Park Grass Experiment) are less close. Two other sites that provide the requisite pre- and post-bomb data are also fitted; a prairie Chernozem from Russia and an annual grassland from California. Roth-PC-1 gives a close fit to measurements of organic C and radiocarbon down the Chernozem profile, provided that allowance is made for soil age; with the annual grassland the fit is acceptable in the upper part of the profile, but not in the clay-rich Bt horizon below. Calculations suggest that treating the top metre of soil as a homogeneous unit will greatly overestimate the effects of global warming in accelerating the decomposition of soil C and hence on the enhanced release of CO2 from soil organic matter; more realistic estimates will be obtained from multi-layer models such as RothPC-1.

Joint modelling of obstacle induced and mesoscale changes: current limits and challenges

Obstacles considerably influence boundary layer processes. Their influences have been included in mesoscale models (MeM) for a long time. Methods used to parameterise obstacle effects in a MeM are summarised in this paper using results of the mesoscale model METRAS as examples. Besides the parameterisation of obstacle influences it is also possible to use a joint modelling approach to describe obstacle induced and mesoscale changes. Three different methods may be used for joint modelling approaches: The first method is a time-slice approach, where steady basic state profiles are used in an obstacle resolving microscale model (MiM, example model MITRAS) and diurnal cycles are derived by joining steady-state MITRAS results. The second joint modelling approach is one-way nesting, where the MeM results are used to initialise the MiM and to drive the boundary values of the MiM dependent on time. The third joint modelling approach is to apply multi-scale models or two-way nesting approaches, which include feedbacks from the MiM to the MeM. The advantages and disadvantages of the different approaches and remaining problems with joint Reynolds-averaged Navier–Stokes modelling approaches are summarised in the paper.

The underlying return generating factors for REIT returns: an application of independent component analysis

Multi-factor approaches to analysis of real estate returns have, since the pioneering work of Chan, Hendershott and Sanders (1990), emphasised a macro-variables approach in preference to the latent factor approach that formed the original basis of the arbitrage pricing theory. With increasing use of high frequency data and trading strategies and with a growing emphasis on the risks of extreme events, the macro-variable procedure has some deficiencies. This paper explores a third way, with the use of an alternative to the standard principal components approach – independent components analysis (ICA). ICA seeks higher moment independence and maximises in relation to a chosen risk parameter. We apply an ICA based on kurtosis maximisation to weekly US REIT data using a kurtosis maximising algorithm. The results show that ICA is successful in capturing the kurtosis characteristics of REIT returns, offering possibilities for the development of risk management strategies that are sensitive to extreme events and tail distributions.