Conjoint choice experiments are used widely in marketing to study consumer preferences amongst alternative products. We develop a class of choice models, belonging to the class of Poisson race models, that describe a ‘random utility’ which lends itself to a process-based description of choice. The models incorporate a dependence structure which captures the relationship between the attributes of the choice alternatives and which appropriately moderates the randomness inherent in the race. The new models are applied to conjoint choice data and are shown to have performance markedly superior to that of independent Poisson race models and of the multinomial logit model.

Customer preference modelling has been widely used to aid engineering design decisions on the selection and configuration of design attributes. Recently, network analysis approaches, such as the exponential random graph model (ERGM), have been increasingly used in this field. While the ERGM-based approach has the new capability of modelling the effects of interactions and interdependencies (e.g., social relationships among customers) on customers’ decisions via network structures (e.g., using triangles to model peer influence), existing research can only model customers’ consideration decisions, and it cannot predict individual customer’s choices, as what the traditional utility-based discrete choice models (DCMs) do. However, the ability to make choice predictions is essential to predicting market demand, which forms the basis of decision-based design (DBD). This paper fills this gap by developing a novel ERGM-based approach for choice prediction. This is the first time that a network-based model can explicitly compute the probability of an alternative being chosen from a choice set. Using a large-scale customer-revealed choice database, this research studies the customer preferences estimated from the ERGM-based choice models with and without network structures and evaluates their predictive performance of market demand, benchmarking the multinomial logit (MNL) model, a traditional DCM. The results show that the proposed ERGM-based choice modelling achieves higher accuracy in predicting both individual choice behaviours and market share ranking than the MNL model, which is mathematically equivalent to ERGM when no network structures are included. The insights obtained from this study further extend the DBD framework by allowing explicit modelling of interactions among entities (i.e., customers and products) using network representations.

Young Canadian women engage in post-school study at a much higher rate than their Australian peers, with a large part of the difference in this rate attributable to differences in rates of participation in the non-university sector. This article uses data from the Australian Longitudinal Surveys of Australian Youth and the Canadian Youth in Transition Survey to generate a unique cross-country comparison of the characteristics of young women engaged in different types of post-school education. The results highlight important differences in the role played by academic ability and parental resources in the allocation of educational ‘slots' in the non-university sectors of the two countries. The results suggest that ‘second-tier’ post-school institutions could play a role in boosting rates of post-school education in Australia, with important consequences for the design of policy on this sector.

In this note, we consider dynamic assortment optimization with incomplete information under the capacitated multinomial logit choice model. Recently, it has been shown that the regret (the cumulative expected revenue loss caused by offering suboptimal assortments) that any decision policy endures is bounded from below by a constant times $\sqrt {NT}$, where $N$ denotes the number of products and $T$ denotes the time horizon. This result is shown under the assumption that the product revenues are constant, and thus leaves the question open whether a lower regret rate can be achieved for nonconstant revenue parameters. In this note, we show that this is not the case: we show that, for any vector of product revenues there is a positive constant such that the regret of any policy is bounded from below by this constant times $\sqrt {N T}$. Our result implies that policies that achieve ${{\mathcal {O}}}(\sqrt {NT})$ regret are asymptotically optimal for all product revenue parameters.

Recently, there has been much interest among horticultural producers concerning the marketing of organic and locally produced food. A consumer survey was administered that asked respondents to choose an applesauce product from a list of products differentiated by price, and by labels that described fat content, nutrition content, and whether the product was grown organically and/or locally. Our analysis indicates that consumers were willing to pay more for locally grown applesauce compared to applesauce that was labeled USDA Organic, Low Fat, or No Sugar Added. Furthermore, we find evidence that increased knowledge of agriculture decreases the willingness to pay for organic and locally grown applesauce.

This paper reports results from a U.S. national telephone survey ongenetically modified foods (vegetable oil, cornflakes, and salmon). Thesurvey featured a contingent valuation in which respondents chose betweenthe GM and non-GM alternatives with an option of indifference. The binomialand multinomial logit models yielded estimated willingness to pay (WTP) toavoid the GM alternatives. Respondents were willing to pay 20.9%, 14.8%,28.4%, and 29.7% of the base prices to avoid GM vegetable oil, GMcornflakes, GM-fed salmon, and GM salmon, respectively. The inclusion ofindifference option could increase the sample size and moderate the meanWTP.

Adoption of conservation tillage can lead to substantial environmental benefits from reduced soil erosion. But benefits may be partially offset if adoption increases reliance on agricultural chemicals. Using area study data from the Cornbelt, this study examines factors affecting adoption of no-till and other conservation tillage systems and their effect on chemical use and corn yield. The results find no evidence that herbicide or fertilizer application rates are higher on fields with conservation tillage systems compared with conventional tillage. However, insecticide use may increase somewhat and yield may be lower. Current demographic trends in U.S. agriculture favor continued diffusion of conservation tillage.

A multinomial logit is utilized to model the choice of whether to purchase yield or revenue insurance using subjectively elicited survey data. Our results indicate that the demand for crop insurance is inelastic (−0.40), consistent with most earlier yield elasticity estimates, but the elasticity for choices between yield and revenue insurance is found to be relatively more elastic (−0.88).