روش های قیمت لذت باورانه و ساختار فناوری بالای بازارهای صنعتی : تجزیه و تحلیل تجربی

This article develops a hedonic price model to investigate empirically the structure of a rapidly evolving industrial market. The model postulates price distortions that arise out of intersegment and interfirm heterogeneity. The application of the model supplies evidence in support of the hypotheses. Empirical results are consistent with existing work on the role of technical performance and technological change in hedonic evaluations of high-technology industrial products. Particular emphasis is placed on policy implications for industrial marketing management.

This paper examines the implications of intersegment and interfirm differences for the price structure of a high-technology market and shows how differences both among segments and among vendors can lead to price discrimination strategies. In industrial markets, competition often is based on differences in product performance. In high-technology markets, the rate at which product performance changes is often rapid, making it vital for firms to keep abreast of technological change. Observed differences in product prices therefore might be explained solely by differences in product performance, at any one moment in time or by changes in quality over time. However, our study illustrates that these are not the only determinants of price structure. More specifically, we argue that differences in price sensitivities among customer segments can lead to price discrimination schemes in which firms can charge significant price premiums. Such premiums are charged over and above any allowance made for differences in product performance. Furthermore, despite an emphasis on competition based on technological performance in such markets, manufacturer names and differences in reputations also affect their ability to charge price premiums. Our study indicates that price premiums are charged over performance-corrected prices, which we hypothesize arise from unobserved marketing capabilities that differ among firms. For the empirical identification of the above relationships, we apply hedonic price methods to data describing the computer hard disk drive market. As shown below, the application of the hedonic framework provides evidence in support of the hypotheses along with useful empirically determined insights. The organization of the article is as follows. The next section provides a brief overview of the computer disk drive industry considered here and lays the principles of the hedonic approach to the analysis of differentiated markets. The third section develops an empirical framework and derives a hedonic model that describes our hypotheses. Empirical results are presented in the fourth section. Subsequently, we discuss the empirical findings and their implications for industrial marketing management. A concluding section summarizes the study.

In this article, we have been concerned with the price structure of high-technology markets. From a managerial point view, the empirical analysis highlights the role of segmentation schemes that may arise out of heterogeneous end user applications. The findings also suggest the existence of manufacturer name premiums that cannot be explained in terms of technological advantage and reflect the marketing clout of the manufacturer. From a methodological standpoint, the present model addresses the problem of interfirm heterogeneity and demonstrates simple ways to deal with segment-specific hedonic price surfaces. In addition, the current approach provides the marketer with considerably more information and analytical insights than the commonly used price-performance ratios and curves 30 and 31. In applied business marketing research, our empirical framework can be invoked to assist fine-tuning of industrial marketing effort. Buyers and suppliers of high-technology components need to understand how specific product attributes, technological progress, and heterogeneity determine the price structure of the market. Optimization of marketing mix requires such empirically determined insights. For example, a market-driven price for a new model can be determined using the hedonic model, and the actual price of a current product can be assessed vis-à-vis its predicted competitive level. Furthermore, implicit characteristic prices, i.e., the parameters of a hedonic regression, would allow management to assess the relative payoff of performance attributes and evaluate the profitability of new product specifications. The usefulness and adaptability of this model can be further demonstrated by applying it to other marketing contexts. The model is sufficiently generalized to accommodate a variety of industrial products as long as performance related dimensions can be identified and measured. Finally, the foregoing discussion suggests that the hedonic function describes equilibrium prices that are determined by demand and supply functions for product characteristics. Further work on the empirical identification of such demand-supply relationships would be rewarding [32]. Models that deal simultaneously with both sides of the market can surely shed more light in the internal structure of high-technology industrial markets.