Reduce Demand Uncertainty Research Articles

Applying Hedonic Pricing Models and Factorial Surveys at Parker Pen to Enhance New Product Success

Walking the path from new product concept to successful commercialization is a tightrope act. Product developers must carefully balance a variety of factors, including predictions of consumer price sensitivity as well as which combination of product attributes will be most valued by the intended market. A well‐chosen mix of analytical tools can enhance a firm's chances of accurately predicting market demand.Chuck Tomkovick and Kathryn E. Dobie describe how the integration of two product attribute assessment techniques–hedonic pricing models and factorial surveys–allows product designers to more accurately gauge price sensitivity and market receptivity to new product designs. They also describe how these analytical tools were used to improve decision‐making in product development at the Parker Pen Company, and they discuss the role these tools can play in facilitating the transition from concept to commercialization.Hedonic price analysis is an econometric method for determining the value purchasers place on attributes of existing products. In product development, factorial surveys are used to identify the value members of the target market place on new product concepts and prototypes. When used in combination with identified hedonic prices, the responses to a factorial survey allow product developers to predict consumer willingness‐to‐pay for various combinations of new product attributes.Following development of prototypes for two new product lines, product developers at the Parker Pen Company used hedonic pricing models and factorial surveys as a means for reducing demand uncertainty and for clarifying what consumers were willing to pay for various combinations of product attributes that were under consideration. The integration and use of these techniques involved a five‐step process of target market identification, product attribute identification, hedonic price estimation, administering of the factorial survey, and determination of consumer willingness‐to‐pay. The results of these analyses allowed Parker Pen to better focus product development efforts on those design elements for which test market customers indicated both demand and willingness‐to‐pay.The Parker Pen Company found hedonic pricing and factorial surveys useful for predicting both the rate and the degree of change in consumers' marginal utility for specific product attributes. The usefulness of these techniques also extends beyond the early stages of new product conception. These techniques are helpful in the development and implementation of dynamic new product marketing mix strategies, including such elements as product design, pricing, channel selection, and promotion.

Applying hedonic pricing models and factorial surveys at Parker Pen to enhance new product success

Walking the path from new product concept to successful commercialization is a tightrope act. Product developers must carefully balance a variety of factors, including predictions of consumer price sensitivity as well as which combination of product attributes will be most valued by the intended market. A well-chosen mix of analytical tools can enhance a firm's chances of accurately predicting market demand. Chuck Tomkovick and Kathryn E. Dobie describe how the integration of two product attribute assessment techniques—hedonic pricing models and factorial surveys—allows product designer to more accurately gauge price sensitivity and market receptivity to new product designs. They also describe how these analytical tools were used to improve decision-making in product development at the Parker Pen Company, and they discuss the role these tools can play in facilitating the transition from concept to commercialization. Hedonic price analysis is an econometric method for determining the value purchasers place on attributes of existing products. In product development, factorial surveys are used to identify the value members of the target market place on new product concepts and prototypes. When used in combination with identified hedonic prices, the responses to a factorial survey allow product developers to predict consumer willingness-to-pay for various combinations of new product attributes. Following development of prototypes for two new product lines, product developers at the Parker Pen Company used hedonic pricing models and factorial surveys as a means for reducing demand uncertainty and for clarifying what consumers were willing to pay for various combinations of product attributes that were under consideration. The integration and use of these techniques involved a five-step process of target market identification, product attribute identification, hedonic price estimation, administering of the factorial survey, and determination of consumer willingness-to-pay. The results of these analyses allowed Parker Pen to better focus product development efforts on those design elements for which test market customers indicated both demand and willingness-to-pay. The Parker Pen Company found hedonic pricing and factorial surveys useful for predicting both the rat and the degree of change in consumers' marginal utility for specific product attributes. The usefulness of these techniques also extends beyond the early stages of new product conception. These techniques are helpful in the development and implementation of dynamic new product marketing mix strategies, including such elements as product design, pricing, channel selection, and promotion.

Market segmentation and oligopoly under uncertainty

The paper considers an oligopoly under uncertainty in segmented markets (markets in which risk aversion may vary across firms). With strong segmentation, a firm (rival) will increase (decrease) output and value in response to an increase in demand uncertainty. With weak segmentation, firms' outputs and values decrease with an increase in demand uncertainty. Thus, the plausible suspicion that decreasing demand uncertainty is beneficial to the participants may not be true in strongly segmented markets. A logical inference is that not concealing information about a random element in demand (i.e., reducing demand uncertainty) is the dominant strategy with weak segmentation.