Recreation Nonparticipation as Choice Behavior Rather Than Statistical Outcome

In recreation demand models nonparticipation is usually estimated as the probability mass on zero demand given a positive level of expected demand and a discrete distribution of demand outcomes. Researchers have attempted to improve predictions of nonparticipation by modifying the parameters of the demand distribution. This study departs from previous approaches by explicitly incorporating nonparticipation into the behavioral model. The choice to participate is described by a distribution of preferences combined with a choke price on individual demands to distinguish participants from nonparticipants. The model is found to accurately predict nonparticipation and the size of the user group.     

A weighted logit freight mode-choice model

The paper describes the estimation of a weighted discrete choice model applicable for analysing choice of mode and crossing for freight in the Oresund region. The study finds that, by applying a weighted logit approach, it is possible to establish a suitable decoupling of agents and shipments. Moreover, by assessing preferences on the basis of a representative baseline OD matrix it is possible to better reflect the dependence between mode substitution effects and geography/infrastructure. The paper presents demand elasticities with respect to monetary cost and travel time as well as value-of-time estimates for five modes and thirteen commodity groups.     

On the Similarity of Classical and Bayesian Estimates of Individual Mean Partworths

An exciting development in modeling has been the ability to estimate reliable individual-level parameters for choice models. Individual partworths derived from these parameters have been very useful in segmentation, identifying extreme individuals, and in creating appropriate choice simulators. In marketing, hierarchical Bayes models have taken the lead in combining information about the aggregate distribution of tastes with the individual's choices to arrive at a conditional estimate of the individual's parameters. In economics, the same behavioral model has been derived from a classical rather than a Bayesian perspective. That is, instead of Gibbs sampling, the method of maximum simulated likelihood provides estimates of both the aggregate and the individual parameters. This paper explores the similarities and differences between classical and Bayesian methods and shows that they result in virtually equivalent conditional estimates of partworths for customers. Thus, the choice between Bayesian and classical estimation becomes one of implementation convenience and philosophical orientation, rather than pragmatic usefulness.     

Quality certification vs. product traceability: Consumer preferences for informational attributes of pork in Georgia

Consumer willingness-to-pay for informational attributes of food products is important information for food producers and supply chain participants and policy makers. We examine consumer demand in the pork sector of the Republic of Georgia. Results of conditional and mixed logit estimation, conducted on choice experiment data, reveal that Georgian consumers treat quality certification and product traceability attributes as substitutes. We also find that producers and other supply chain participants should be concerned primarily with maintaining the appearance of pork products. Retailer specific factors such as location and type of outlet can also substitute for product traceability. Store location and product appearance, however, are complementary attributes. In light of the recent turbulence in Georgia these consideration may be of paramount importance as participants in the supply chain seek to rebuild damaged infrastructure.     

Environmental diversity in recreational choice modelling

The accuracy of environmental valuation studies relies, to a great extent, on the suitability of the proxy measures used to capture individuals' preferences. While important advances have been achieved in the last years concerning the characterization of the physical background in which recreational choices are made, Travel Cost Method applications have failed to consider the heterogeneity of landscape and the spatial configuration of land use. This paper presents an empirical application to forest recreation in Mallorca (Spain), implementing a random parameter logit model to evaluate in terms of goodness-of-fit, model predictions and welfare measurements the effects of environmental diversity on the recreational site-choice process.     

A conjoint analysis of farmer preferences for community forestry contracts in the Sumber Jaya Watershed, Indonesia

A wide range of policy instruments have been devised and applied to support the goals of sustainable forestry management. Community forestry programs can contain elements of several of those instruments. This paper considers the design of community forestry contracts in the Sumber Jaya area of Indonesia where community forestry contracts are agreements between the Forestry Department and community groups that provide group members with time-bound leasehold rights to protection forests, on the condition that farmers abide by specified land-use restrictions and pay any required fees. Farmers perceive that the contracts represent a bundle of restrictions and inducements, some of which are explicitly stated in the contract and others that are implied by the contract. Conjoint analysis was used to quantify farmers' tradeoffs among the explicit and implicit attributes of the contracts. The results of logit and ordered logit models show that farmers are most concerned about the length of the contract, and relatively unconcerned about requirements on tree density and species composition. An implicit attribute, greater access to forestry and agroforestry extension, emerges as an important implicit attribute. The results imply that farmers in this part of Indonesia would be willing to abide by fairly strict limitations on land use, provided that they can be assured of long-term rights to the planted trees.     

Data pruning in consumer choice models

Common, if not ubiquitous, Marketing practice when estimating models for scanner panel data is to: (a) observe the data, (b) prune the data to a “manageable” number of brands or SKUs, and (c) fit models to the remaining data. We demonstrate that such pruning practice can lead to significantly different (and potentially biased) elasticities, and hence different managerial/practical outcomes, especially in the context of model misspecification. We first justify our claims theoretically by writing the general problem in a classic missing-data framework and demonstrate that commonly used pruning mechanisms (gleaned from current academic Marketing literature) can lead to a nonignorable missing data mechanism. Secondly, we summarize an extensive set of simulations that were run to understand the driving factors of that bias. The results indicate much greater pruning bias in those cases where model fit is poor (small ), random utility errors are correlated with the covariates, or the model is misspecified (e.g., a homogeneous logit is specified when a mixed-logit is true). Empirically, we also demonstrate our findings on the well-cited and highly utilized fabric softener data of Fader and Hardie (1996). Our empirical findings suggest a number of estimates that vary according to the way in which the data is pruned including the magnitude of market mix and attribute elasticities, and purchase probabilities, but that the pruning effect is smaller for better fitting models.

Conjoint and WTP analyses of future mobile phones for digital convergence

Digital convergence for mobile phones is a hot issue. This study considers future development of mobile phones with a view toward consumers' usage and the amount they are willing to pay. In order to select preferable convergence technology, we utilize convergence concepts such as absorption, blending, and combination. The result of conjoint analysis shows that a preference for convergence technology will involve computing, media, navigation, and imaging. However, only the computing attribute increases consumers' willingness to pay. Our study results contribute to product planning and commercialization of innovative mobile phones.     

Anti-poverty competences in a multilevel government: an empirical analysis of citizens’ preferences in Europe

This article aims to investigate individuals’ perceptions about institutions that should be primarily responsible for reducing or preventing poverty, which is a dramatic phenomenon that became a crucial issue in European countries over recent years. We propose an empirical analysis based on European survey data and investigate some citizens’-level and country-level variables that potentially affect individuals’ attitudes. Our results suggest that country-level economic and institutional characteristics do significantly affect individual preferences for the governance of anti-poverty policies.     

On Corporate Divestiture

This paper investigates why firms choose to divest their units/segments, and how firms choose among the three divestiture mechanisms (equity carveout, spinoff, and asset selloff). A direct comparison is conducted on firms viable choices on a comprehensive sample of corporate divestiture transactions in the period of 1985-1998. Our multinomial logit analysis provides a complete picture on corporate divestitures. We find that, in support for the focusing hypothesis, highly diversified firms are more likely to divest units when suffering from low operating efficiency. Our results are also consistent with the proposition that firms are divesting to relax their credit constraint, as firms with higher leverage ratios and low cash income are more likely to engage in carveouts or selloffs. We find limited evidence of information asymmetry as the major determinant of divestitures. We provide new findings on firms choice among the three divestiture options. We report that, conditioned on the decision to divest, firms mainly use asset selloffs in divesting smaller units operating in the same industry. Firms with larger divested units are more likely to use spinoff or carveout transactions. Parent firms having high revenue growth, high book-to-market ratio, and divesting unit when market sentiment is high are less likely to use spinoffs. Firms having high dividend yield, less information asymmetry, and divesting units operating in different industries are more likely to use carveout as an exit mechanism. Alternative specification of an ordered logit analysis generates consistent findings.JEL Classification: G34