767,840 research outputs found
[Handwritten list of names by an unknown author #1]
No full textHandwritten note by an unknown author, listing various names
Modelling individual preferences, State of the art, recent advances and future directions.
No full textDespite the above famous statement, individuals have always disputed about individual tastes, and the decision making processes behind consumers’ choices has been a focal interest for decades. Although challenges against the theory of rational behaviour date back to the work of von Neumann and Morgenstern (1944), the dominating approach (at least in the transport field) has been the neoclassical economics assumption of rational decision makers (or even more extreme homo economicus), who always perform well planned and consistent activities, aiming to maximize some subjective measure of value (McFadden, 1999). The reason for this dominance is that economic theory has provided an elegant, rigorous and at the same time relatively easy to implement model, designed to describe individuals’ decisions and to provide quantitative forecasts with well-defined statistical properties. On the other hand, although investigations in psychology have made an impression on economic thought1 , they have tended to generate lists of errors and biases and have mostly failed (with excellent exceptions) to offer a coherent alternative to the rational-agent model (Kahneman, 2003). Psychologists recognise that this complaint is justified, at least partly, because intuitive thought cannot match the elegance and power of formal normative models. However, as Kahneman (2003) points out … “the alternative to simple and precise models is not chaos; psychology offers integrative concepts and mid-level generalizations, which gain credibility from their ability to explain ostensibly different phenomena in diverse domains”. The origin of this divergence relies on the historically different views of the decision-making process between neoclassical economics and psychology. While economists have been interested in mapping from information inputs to choice, treating the decision process as a black box, psychologists’ prime objective has been to understand what happens inside that black box: the nature of these decision elements, how they are established and modified by experience, and how they determine values. McFadden (1999) notes that what has made the distance between the two approaches even bigger is that psychologists view the decision process as dynamic and individual behaviour as local, adaptive, learned, dependent on context, mutable and influenced by complex interactions of perceptions, motives and attitudes. On the other hand, in the economic tradition preferences are primitive, consistent, and immutable (preference rationality), consumers behave as if they possess the formal tools with which to calculate the optimum adequately (perception-rationality), and the cognitive process is simply preference maximization, given market constraints (process-rationality). The models that we (transport researchers) currently use to describe how people choose among a discrete set of alternatives are based on these assumptions of rationality in preference, perception and process. McFadden’s work (1978; 1981) on Generalised Extreme Value (GEV) formulation, which generalised the work of Williams (1977), provides a rigorous foundation for consumer choice modelling derived from economic theory. Although the original formulation of the random utility maximisation (RUM) as a behavioural model followed the economists’ theory of consumer behaviour, it also included “features of the taste template that were heterogeneous across individuals and unknown to the analyst, as well as unobserved aspects of experience and of information on the attributes of alternatives, interpreted as random factors” (McFadden, 2000). This led to the paradigm for generating discrete-choice models (DCM), commonly reported in textbooks (Ben-Akiva and Lerman, 1985; Ortúzar and Willumsen, 2011; Train, 2009), that the random part of the individual utility reflects the modellers’ lack of complete information about all the elements considered by the individual making a choice, which might also include unobserved deviations of individual behaviour from perfect rationality. This paradigm posed the bases for the most important stream of research of the last 30 years. Since McFadden’s work, in fact, research activity in this field has been very proactive. Major progress has been made in exploring the potentiality of DCM to improve the ability to effectively reproduce individual behaviour. In particular, this paper draws attention to two streams of research motivated by this work. The first refers to the microeconomic justification of DCM and, in particular, of the utility individuals associate to each discrete alternative. The second stream, and maybe the most productive one, has been concerned with the characterization of the error terms, and in particular the exploitation of the mixed multinomial logit (MMNL) model. Research in both streams has aimed to improve the representation of the true phenomenon. However, the goal has always been that the measurable part of utility should be able to explain (as much as possible) the true behaviour in order to reduce the explanatory power left in the error term. This is correct except that, under the neo-classical theory, the systematic measurable utility was associated only with “rational” behaviour and what deviated from it was classified as error and hence minimised. Unfortunately, major improvements in model fit obtained with complex decompositions of the error term have given a strong signal that there are inherent limitations in the capability of microeconomic theory to explain individual choices and that we are still far from having a satisfactory representation (through known variables) of the real phenomenon. In fact, although RUM “takes a nod towards psychological theory” (Batley and Daly, 2006), the error term cannot be considered to properly explain behaviour that departs from perfect rationality. This is because errors are parameterized in terms of statistical distributions and the psychological concept of irrationality (i.e., not rational in the sense of neoclassical economic theory) is associated to the concept of randomness. As suggested by Ariely (2008), apparent irrationality can indeed be explained and predicted. Illustrious scholars (McFadden, 2000; Ben-Akiva, et al, 2002a) have strongly asserted the need to explore more seriously the suggestions provided by the psychological literature. After a shy start, the last decade has seen a surprising increase in the amount of work in this area (see for example Walker, 2001; Gärling and Axhausen, 2003; Bonsall, et al, 2007). Most of it has concentrated on demonstrating empirically that integrating psychology theory into the economic framework results in tangible improvement in terms of model fit, and interestingly most of it has been based on the MMNL structure. This is a key point, because the last years have also witnessed an increased awareness of the inherent limitations of the MMNL in terms of both estimation and especially prediction. In fact, notwithstanding the clear ability of this model to represent an ample range of behaviours via error term decomposition, several problems implicit in its structure have led analysts to lose confidence in the model. It is interesting then to understand whether or not these new models, which go beyond the rational postulate, still suffer from the above limitations or to what extent these are overcome. This paper presents a critical review of the research developments in the representation of the decision process, and it is structured into two parts. The first is dedicated to reviewing the limitations of the DCM and, in particular, of the MMNL model. Limits due to both the microeconomic theory of the rational user and the exploitation of the error terms will be critically discussed. The second part of the paper reviews research belonging to the non-rational theory. I concentrate on those advances that still rely heavily on the DCM with the aim to discuss to what extent we are really moving forward with respect to the above limitations of the classical MMNL model. Although focusing on research produced in the transport field, the paper provides and relies on several references from the literature in psychology and behavioural economics. Placing an accent on the limitations of current theory is not dictated by a pessimist view. On the contrary, it is intended as a proactive approach; these limitations constitute the starting point for and, above all, should stimulate new research. Another important consideration is that excellent reviews of both microeconomic theory (see McFadden, 2000; Bates, 2007; Jara-Díaz, 2007) and discrete choice models (see Ben-Akiva, et al, 2002b; Ortúzar, 2006; Bhat, 2007) already exist, while a review of their limitations seems yet to be undertaken; at least this is what emerges from research conducted over the last few years. The paper concludes by discussing some open questions raised by the research conducted so far and giving some final thoughts about the amazing challenge unfolding before us over the next years.<br/
Mapping the Discipline of the Olympic Games An Author-Cocitation Analysis
No full textThe authors conducted an author cocitation analysis on prominent authors writing about the Olympics during the 1990s. Author cocitation is an established bibliometric technique that can be used to measure the relative similarities of topics written about by the cited authors. This enables a visual representation of the “intellectual space” of the discipline, in this case the Olympics, to be created for the period under review. So core and peripheral research areas are identified, along with their major contributors. The representation appears as a two-dimensional cluster-enhanced map. Subject expertise was then applied to the results to place labels on the generated clusters of authors and their topics
Appropriate Similarity Measures for Author Cocitation Analysis
No full textWe provide a number of new insights into the methodological discussion about author cocitation analysis. We first argue that the use of the Pearson correlation for measuring the similarity between authors’ cocitation profiles is not very satisfactory. We then discuss what kind of similarity measures may be used as an alternative to the Pearson correlation. We consider three similarity measures in particular. One is the well-known cosine. The other two similarity measures have not been used before in the bibliometric literature. Finally, we show by means of an example that our findings have a high practical relevance.information science;Pearson correlation;cosine;similarity measure;author cocitation analysis
Variations on the Author
No full text“Variations on the Author” discusses two of Eduardo Coutinho’s recent films (Um Dia na Vida, from 2010, and Últimas Conversas, posthumously released in 2015) and their contribution to the general question of documentary authorship. The director’s filmography is characterized by a consistent yet self-effacing form of authorial self-inscription: Coutinho often features as an interviewer that rather than express opinions propels discourses; an interviewer that is good at listening. This mode of self-inscription characterizes him as an author who is not expressive but who is nonetheless markedly present on the screen. In Um Dia na Vida, however, Coutinho is completely absent form the image, while Últimas Conversas, on the contrary, includes a confessional prologue that moves the director from the margins to the center of his films. This article examines the ways in which these works stand out in the filmography of a director who offers new insights into the notion of cinematic authorship
The genus Eurymeros Bhat (Hymenoptera, Braconidae, Alysiinae) newly recorded from China
No full textAlysiinae Leach is a species-rich subfamily in Braconidae, of which several species play an important role in biological control. The monotypic genus Eurymeros tumespiraculum Bhat, 1980 was discovered in Tibet and Yunnan provinces for the first time, representing the first record of the genus Eurymeros Bhat, 1980 (Braconidae, Alysiinae) in China.The rare genus Eurymeros Bhat, 1980 (Braconidae, Alysiinae) and its only known species, E. tumespiraculum Bhat, 1980, are newly recorded from China. The morphological variation of the Chinese specimens is described and illustrated
Going Beyond Counting First Authors in Author Co-citation Analysis
No full textThe present study examines one of the fundamental aspects of author co-citation analysis (ACA) - the way co-citation
counts are defined. Co-citation counting provides the data on which all subsequent statistical analyses and mappings
are based, and we compare ACA results based on two different types of co-citation counting - the traditional type that
only counts the first one among a cited work's authors on the one hand and a non-traditional type that takes into
account the first 5 authors of a cited work on the other hand. Results indicate that the picture produced through this non-traditional author co-citation counting contains more coherent author groups and is therefore considerably clearer. However, this picture represents fewer specialties in the research field being studied than that produced through the traditional first-author co-citation counting when the same number of top-ranked authors is selected and analyzed. Reasons for these effects are discussed
[Report to Chief J. E. Curry, by an unknown author #2]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
[Report to Chief J. E. Curry, by an unknown author #1]
No full textReport to Chief J. E. Curry, by an unknown author. The report contains a list of officers who gave depositions to the United States Attorney
The role of precision medicine in liver transplantation: An interview with Dr. Mamatha Bhat
No full textDr. Mamatha Bhat is a Hepatologist and Clinician-Scientist affiliated with the Ajmera Transplant Centre at the University Health Network (UHN). She is also a scientist at the Toronto General Hospital Research Institute (TGHRI) and an Associate Professor of Medicine at the University of Toronto. Dr. Bhat serves as Director of the Clinician-Scientist Training Program for the Department of Medicine, Partnership & Engagement Lead for the Temerty Centre for AI Research and Education in Medicine (T-CAIREM), and past Chair of the International Liver Transplant Society Basic and Translational Science Research Committee.
Dr. Bhat completed her medical training at McGill University. She then completed a Transplant Hepatology fellowship at the Mayo Clinic. This was followed by a CIHR Fellowship for Health Professionals, through which she completed a PhD in Medical Biophysics.
Dr. Bhat’s research program aims to improve long-term outcomes for patients undergoing liver transplantation by developing artificial intelligence tools that integrate clinical and omics data. Her vast contributions to the field of liver transplant research have been recognized internationally
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