A comparison of generalized multinomial logit, random parameters logit, wtp-space and latent class models to studying consumers' preferences for animal welfare

The European societies are requiring that animals to be raised as closely as possible to their natural conditions. The growing concerns about animal welfare is resulting in continuous modifications of regulations and policies that led to ban of a number of intensive farming methods. The European authorities consider the pig welfare as a priority issue. They are studying to ban surgical pig castration by 2018, which may seriously affect markets and consumers due to boar tainted-meat. This study analysed consumers’ preferences and acceptance regarding an alternative to castration of high-level boar-taint frankfurter sausages. Non-hypothetical discrete choice experiments was applied by creating a real shopping scenario before and after tasting the products. Data were collected for a sample of 150 consumers from the metropolitan area of Madrid, Spain. Different modelling approaches (Generalized Multinomial Logit-GMNL, Random Parameters Logit-RPL, WTP-space and Latent Class-LC models) were applied to figure out which model have the best goodness of fit. Results showed the appropriateness of the proposed alternative by using a new flavour as a masking strategy. When consumers tasted the products, they showed their willingness to pay a premium for this flavour. The WTP space model showed the best goodness of fit in terms of likelihood, Akaike information criterion and McFadden Pseudo R2. Furthermore, the degree of randomness identified by the scale parameter is also estimated. Uncertainty in selection decreased significantly after the sensory experiencePostprint (published version

Tree biomass equations from terrestrial LiDAR : a case study in Guyana

Large uncertainties in tree and forest carbon estimates weaken national efforts to accurately estimate aboveground biomass (AGB) for their national monitoring, measurement, reporting and verification system. Allometric equations to estimate biomass have improved, but remain limited. They rely on destructive sampling; large trees are under-represented in the data used to create them; and they cannot always be applied to different regions. These factors lead to uncertainties and systematic errors in biomass estimations. We developed allometric models to estimate tree AGB in Guyana. These models were based on tree attributes (diameter, height, crown diameter) obtained from terrestrial laser scanning (TLS) point clouds from 72 tropical trees and wood density. We validated our methods and models with data from 26 additional destructively harvested trees. We found that our best TLS-derived allometric models included crown diameter, provided more accurate AGB estimates (R-2 = 0.92-0.93) than traditional pantropical models (R-2 = 0.85-0.89), and were especially accurate for large trees (diameter > 70 cm). The assessed pantropical models underestimated AGB by 4 to 13%. Nevertheless, one pantropical model (Chave et al. 2005 without height) consistently performed best among the pantropical models tested (R-2 = 0.89) and predicted AGB accurately across all size classes-which but for this could not be known without destructive or TLS-derived validation data. Our methods also demonstrate that tree height is difficult to measure in situ, and the inclusion of height in allometric models consistently worsened AGB estimates. We determined that TLS-derived AGB estimates were unbiased. Our approach advances methods to be able to develop, test, and choose allometric models without the need to harvest trees

Bayesian networks to explain the effect of label information on product perception

Interdisciplinary approaches in food research require new methods in data analysis that are able to deal with complexity and facilitate the communication among model users. Four parallel full factorial within-subject designs were performed to examine the relative contribution to consumer product evaluation of intrinsic product properties and information given on packaging. Detailed experimental designs and results obtained from analyses of variance were published [1]. The data was analyzed again with the machine learning modelling technique Bayesian networks. The objective of the current paper is to explain basic features of this technique and its advantages over the standard statistical approach regarding handling of complexity and communication of results. With analysis of variance, visualization and interpretation of main effects and interactions effects becomes difficult in complex systems. The Bayesian network model offers the possibility to formally incorporate (domain) experts knowledge. By combining empirical data with the pre-defined network structure, new relationships can be learned, thus generating an update of current knowledge. Probabilistic inference in Bayesian networks allows instant and global use of the model; its graphical representation makes it easy to visualize and communicate the results. Making use of the most of data from one single experiment, as well as combining data of independent experiments makes Bayesian networks for analysing these and similarly complex and rich data set

Implications of heterogeneous fracture distribution on reservoir quality; an analogue from the Torridon Group sandstone, Moine Thrust Belt, NW Scotland

This research was funded by a NERC CASE studentship (NERC code NE/I018166/1) in partnership with Midland Valley. Midland Valley's Move software was used for cross section construction and strain modelling. 3D Field software is acknowledged for contour map creation. Mark Cooper is thanked for constructive comments. Steven Laubach and Bill Dunne are thanked overseeing the editorial process and Magdalena Ellis Curry, Bertrand Gauthier and Arthur Lavenu are thanked for constructive reviews.Peer reviewedPublisher PD

Citizens’ Perceptions of Government Policy Success: A Cross-National Study

What explains citizens’ perceptions of government policy success? To answer this question, we use multilevel modelling strategies to examine data gathered across 21 national samples from the 2006 International Social Survey Programme’s (ISSP) Role of Government IV module. Our dependent variable is an index of perceived governmental policy success in six areas. Our analysis reveals that citizens’ evaluations of the success of public policies vary within countries as well as between countries. Our multilevel models indicate that variation in perceptions within countries is largely a function of individual sociodemographic attributes and political attitudes. In contrast, across country variation in perceptions is mainly a function of the quality of public institutions within a country and, to a lesser extent, prevailing economic conditions. These results suggest that citizens’ perceptions of government are not merely influenced by objective outcomes of public policy, they are also influenced by the degree of procedural fairness, professionalism, and integrity within public institutions

Local spatiotemporal modeling of house prices: a mixed model approach

The real estate market has long provided an active application area for spatial–temporal modeling and analysis and it is well known that house prices tend to be not only spatially but also temporally correlated. In the spatial dimension, nearby properties tend to have similar values because they share similar characteristics, but house prices tend to vary over space due to differences in these characteristics. In the temporal dimension, current house prices tend to be based on property values from previous years and in the spatial–temporal dimension, the properties on which current prices are based tend to be in close spatial proximity. To date, however, most research on house prices has adopted either a spatial perspective or a temporal one; relatively little effort has been devoted to situations where both spatial and temporal effects coexist. Using ten years of house price data in Fife, Scotland (2003–2012), this research applies a mixed model approach, semiparametric geographically weighted regression (GWR), to explore, model, and analyze the spatiotemporal variations in the relationships between house prices and associated determinants. The study demonstrates that the mixed modeling technique provides better results than standard approaches to predicting house prices by accounting for spatiotemporal relationships at both global and local scales

Modelling postharvest quality behaviour as affected by preharvest conditions

Some hundred years ago, wise men decided that preharvest research and applications had to be regarded separated from the postharvest handling and behaviour. Over the years, both areas developed completely separated. Control over both areas was obtained by different companies and advisory boards, with mostly not too good means of communication between them. This decision hampered seriously the consistent and integral development of knowledge on food production and usage. Bridging the gap between all the knowledge and expertise available in the preharvest area of growing food and the postharvest area of storing and processing food, has become and is still becoming more and more important over the last couple of years. In this paper, based on theoretical considerations, on plausible (but unproven) mechanisms and applying the fundamental rules of chemical kinetics, a pathway to deduce general and generic models is developed towards a possible approach to integrate all available knowledge. Still the validity of this approach is not proven. However, a number of examples from both the applied as well as the fundamental point of view are elaborated to indicate such an interaction exists, and to indicate how to tackle the modelling problem. The examples range from physiological disorders like core brown, internal brown, chilling injury and the biological age of individual tomatoes in truss tomatoes as related to the maturity at harves

Rolling stock quality - Improvements and user willingness to pay.

This study has estimated monetary valuations of various types of rolling stock and stock related attributes in relation to each other. It has used a combination of Revealed Preference (RP) and Stated Preference (SP) methods. The estimated monetary valuations of different types of rolling stock do not vary greatly and this contrasts with most of the previous quantitative research findings in this area. The largest valuation of one stock type in relation to another was 39 pence per single trip for the comparison of Wessex electrics and Sprinters. This valuation is equivalent to 4.3% of the average fare paid. With regard to specific rolling stock attributes, this study has examined seating comfort, seating layout, ride quality, ambience, ventilation and noise. The most important attributes were found to be seating comfort, ride quality and ambience. The largest valuation obtained for seat comfort differences was 17 pence per single trip for the comparison of Networkers and Sprinters. This is equivalent to 1.9% of the average single fare. The corresponding figure for ride quality was 13 pence for the comparison of Wessex electrics and Sprinters and for ambience it was 10 pence for the comparison of Networkers and Sprinters. The maximum differences between stock types in terms of seating layout, ventilation and noise were all valued at less than five pence. The results can be generalised to stock types not covered in this research by obtaining ratings on a ten point scale of the relevant train types or specific rolling stock attributes and entering these into the estimated model

UML Class Diagram or Entity Relationship Diagram : An Object Relational Impedance Mismatch

It is now nearly 30 years since Peter Chen’s watershed paper “The Entity-Relationship Model –towards a Unified View of Data”. [1] The entity relationship model and variations and extensions to ithave been taught in colleges and universities for many years. In his original paper Peter Chen looked at converting his new ER model to the then existing data structure diagrams for the Network model. In recent years there has been a tendency to use a Unified Modelling Language (UML) class diagram forconceptual modeling for relational databases, and several popular course text books use UMLnotation to some degree [2] [3]. However Object and Relational technology are based on different paradigms. In the paper we argue that the UML class diagram is more of a logical model (implementation specific). ER Diagrams on theother hand, are at a conceptual level of database design dealing with the main items and their relationships and not with implementation specific detail. UML focuses on OOAD (Object Oriented Analysis and Design) and is navigational and program dependent whereas the relational model is set based and exhibits data independence. The ER model provides a well-established set of mapping rules for mapping to a relational model. In this paper we look specifically at the areas which can cause problems for the novice databasedesigner due to this conceptual mismatch of two different paradigms. Firstly, transferring the mapping of a weak entity from an Entity Relationship model to UML and secondly the representation of structural constraints between objects. We look at the mixture of notations which students mistakenly use when modeling. This is often the result of different notations being used on different courses throughout their degree. Several of the popular text books at the moment use either a variation of ER,UML, or both for teaching database modeling. At the moment if a student picks up a text book they could be faced with either; one of the many ER variations, UML, UML and a variation of ER both covered separately, or UML and ER merged together. We regard this problem as a conceptual impedance mismatch. This problem is documented in [21] who have produced a catalogue of impedance mismatch problems between object-relational and relational paradigms. We regard the problems of using UML class diagrams for relational database design as a conceptual impedance mismatch as the Entity Relationship model does not have the structures in the model to deal with Object Oriented concepts Keywords: EERD, UML Class Diagram, Relational Database Design, Structural Constraints, relational and object database impedance mismatch. The ER model was originally put forward by Chen [1] and subsequently extensions have been added to add further semantics to the original model; mainly the concepts of specialisation, generalisation and aggregation. In this paper we refer to an Entity-Relationship model (ER) as the basic model and an extended or enhanced entity-relationship model (EER) as a model which includes the extra concepts. The ER and EER models are also often used to aid communication between the designer and the user at the requirements analysis stage. In this paper when we use the term “conceptual model” we mean a model that is not implementation specific.ISBN: 978-84-616-3847-5 3594Peer reviewe

Direct and mediated impacts of product and process characteristics on consumers’ choice of organic vs. conventional chicken

There is a lack of research into why consumers value process characteristics. In this study, we test the hypothesis that the impact of process characteristics such as organic and free-range on consumers’ choices of food products is at least partly mediated through expected eating quality or taste expectations. In other words, the process characteristics partly function as cues to (eating) quality. Using a traditional metric conjoint approach based on an additive model, four product characteristics (production method, price, size and information about farmer and rearing conditions) were varied in a fractional factorial conjoint design, creating nine profiles of whole chickens. 384 respondents rated the nine different chickens in terms of taste expectations and willingness to buy. Since the nine records for each respondent are not independent, we used linear mixed modelling for the mediation analysis, We find that, as expected, taste expectations are a strong predictor of willingness to buy. As hypothesized, the impact of both product and process characteristics on willingness to buy is at least partly mediated through taste expectations. Hence, the study shows that process characteristics are important for consumers, not only in and off themselves, but partly because consumers make inferences about eating quality from knowledge about such process characteristics