Similarity in linguistic categorization: The importance of necessary properties

Usage-based models of language propose that the acceptability of an element in a constructional slot is determined by its similarity to attested fillers of that slot (Bybee 2010, ch. 4). However, Ambridge and Goldberg (2008) find that the acceptability of a long-distance-dependency (LDD) question does not correlate with the judged similarity of the matrix verb to think and say, which are by far the most frequently attested fillers of this slot. They propose instead that the acceptability of LDD questions is determined by the degree of fit between the information-structure properties of the matrix verb and those specified by the construction—specifically, the degree to which the matrix verb foregrounds its complement clause. This paper explores the possibility of reconciling this explanation with one based on similarity by suggesting that in this case the relevant aspect of similarity is precisely the verb’s foregrounding of its complement. Evidence for this suggestion comes from psychological research showing that in a categorization task, the similarity of an item to the exemplars of a category is judged primarily with respect to the features common to all category members, as well as from the observation that virtually all attested matrix verbs in LDD questions strongly tend to foreground their complements

Environmental Pollution and Awareness in Pokhara City: A Sociological Perspective

Occasional Papers in Sociology and Anthropology - Volume 6, 200

A finite-population revenue management model and a risk-ratio procedure for the joint estimation of population size and parameters

Many dynamic revenue management models divide the sale period into a finite number of periods T and assume, invoking a fine-enough grid of time, that each period sees at most one booking request. These Poisson-type assumptions restrict the variability of the demand in the model, but researchers and practitioners were willing to overlook this for the benefit of tractability of the models. In this paper, we criticize this model from another angle. Estimating the discrete finite-period model poses problems of indeterminacy and non-robustness: Arbitrarily fixing T leads to arbitrary control values and on the other hand estimating T from data adds an additional layer of indeterminacy. To counter this, we first propose an alternate finite-population model that avoids this problem of fixing T and allows a wider range of demand distributions, while retaining the useful marginal-value properties of the finite-period model. The finite-population model still requires jointly estimating market size and the parameters of the customer purchase model without observing no-purchases. Estimation of market-size when no-purchases are unobservable has rarely been attempted in the marketing or revenue management literature. Indeed, we point out that it is akin to the classical statistical problem of estimating the parameters of a binomial distribution with unknown population size and success probability, and hence likely to be challenging. However, when the purchase probabilities are given by a functional form such as a multinomial-logit model, we propose an estimation heuristic that exploits the specification of the functional form, the variety of the offer sets in a typical RM setting, and qualitative knowledge of arrival rates. Finally we perform simulations to show that the estimator is very promising in obtaining unbiased estimates of population size and the model parameters.Revenue management, estimation, multi-nomial logit, risk-ratio

A randomized concave programming method for choice network revenue management

Models incorporating more realistic models of customer behavior, as customers choosing from an offer set, have recently become popular in assortment optimization and revenue management. The dynamic program for these models is intractable and approximated by a deterministic linear program called the CDLP which has an exponential number of columns. However, when the segment consideration sets overlap, the CDLP is difficult to solve. Column generation has been proposed but finding an entering column has been shown to be NP-hard. In this paper we propose a new approach called SDCP to solving CDLP based on segments and their consideration sets. SDCP is a relaxation of CDLP and hence forms a looser upper bound on the dynamic program but coincides with CDLP for the case of non-overlapping segments. If the number of elements in a consideration set for a segment is not very large (SDCP) can be applied to any discrete-choice model of consumer behavior. We tighten the SDCP bound by (i) simulations, called the randomized concave programming (RCP) method, and (ii) by adding cuts to a recent compact formulation of the problem for a latent multinomial-choice model of demand (SBLP+). This latter approach turns out to be very effective, essentially obtaining CDLP value, and excellent revenue performance in simulations, even for overlapping segments. By formulating the problem as a separation problem, we give insight into why CDLP is easy for the MNL with non-overlapping considerations sets and why generalizations of MNL pose difficulties. We perform numerical simulations to determine the revenue performance of all the methods on reference data sets in the literature.assortment optimization, randomized algorithms, network revenue management.

The customer valuations game as a basis for revenue management

I describe the customer valuations game, a simple intuitive game that can serve as a foundation for teaching revenue management. The game requires little or no preparation, props or software, takes around two hours (and hence can be finished in one session), and illustrates the formation of classical (airline and hotel) revenue management mechanisms such as advanced purchase discounts, booking limits and fixed multiple prices. I normally use the game as a base to introduce RM and to develop RM forecasting and optimization concepts off it. The game is particularly suited for non-technical audiences.Revenue management, teaching, valuations

On equilibria in duopolies with finite strategy spaces

We will call a game a reachable (pure strategy) equilibria game if starting from any strategy by any player, by a sequence of best-response moves we are able to reach a (pure strategy) equilibrium. We give a characterization of all finite strategy space duopolies with reachable equilibria. We describe some applications of the sufficient conditions of the characterization.duopoly, equilibria, revenue management, discrete-choice theory