Journal of Marketing Research (JMR)
Опубликовано на портале: 30-09-2003William P. Putsis Journal of Marketing Research (JMR). 2001. Vol. 38. No. 1. P. 110-119.
Despite the importance of product line management as a competitive tool, empirical research addressing the determinants of firm product line decisions is sparse. This study proposes and empirically estimates a descriptive model of firm product line decisions in the personal computer industry over the period 1981-92. The model incorporates the firm's initial choice of the direction of a product line change. It is shown that there are important substantive insights to be gained by analyzing the product line decision in this fashion. In the personal computer industry, for example, firms expand their product lines when industry barriers are low or market opportunities are perceived to exist. High market share firms aggressively expand their product lines, as do firms with relatively high prices or short product lines. In general, the results highlight the various internal and external factors that influence firms' management of their product lines.
Опубликовано на портале: 29-09-2003Peter J. Danaher Journal of Marketing Research (JMR). 2001. Vol. 38. No. 3. P. 298-313.
The authors examine the rescheduling of television programs to maximize the total ratings for one network across a week. The key idea is to design a choice experiment in which television programs are rescheduled and presented to respondents. Respondents read these program schedules (much like the regular TV Guide listings) and give their preferences, including not watching any of the listed programs. Because there are potentially billions of possible schedules, the authors give a procedure for designing a fractional factorial experiment that can accommodate both programs of varying length and constraints on eligible program times. The authors also develop a latent class multinomial logit model for modeling program preferences and present a validation of our experimental procedure and the model. They also present an empirical test of the procedure in which they use the model to predict ratings for all the possible program schedules, not just those constituting the choice sets. In this example, the optimum schedule increases the predicted total weekly ratings during prime time by 18% for a network. The projected increase in total weekly ratings is achieved without the network needing to purchase any new programs; all it needs to do is reschedule eight programs in its existing prime-time lineup.
Transaction Decoupling: How Price Bundling Affects the Decision to Consume (Декомпозиция сделки: как комплектное ценообразование влияет на потребление) [статья]
Опубликовано на портале: 16-11-2003Dilip Soman Journal of Marketing Research (JMR). 2001. Vol. 38. No. 1. P. 30-45.
На современных рынках практика комплектного ценообразования является повсеместной. Производители и розничные продавцы постоянно предлагают комплектные наборы (из разных или одинаковых продуктов) по специальной комплектной цене. Театральные компании и спортивные команды предлагают сезонные билеты. Club Med предлагает отпускные пакеты, включающие авиабилет, проживание и пропитание. Макдональдс предлагает комплексные наборы, которые включают сэндвич, напиток, и обжаренную картошку, а винно-водочные магазины продают вино ящиками по специальным ценам.
Опубликовано на портале: 29-09-2003David H. Henard Journal of Marketing Research (JMR). 2001. Vol. 38. No. 3. P. 362-375.
Product innovation is increasingly valued as a key component of the sustainable success of a business's operations. As a result, there has been a noticeable increase in the number of studies directed at explicating the drivers of new product success. To help managers and researchers synthesize this growing body of evidence, the authors conduct a meta-analysis of the new product performance literature. Of the 24 predictors of new product performance investigated, product advantage, market potential, meeting customer needs, predevelopment task proficiencies, and dedicated resources, on average, have the most significant impact on new product performance. The authors also find that the predictor-performance relationships can vary by measurement factor (e.g., the use of multi-item scales, subjective versus objective measures of performance, senior versus project management reporting, time elapsed since product introduction) or contextual factor (e.g., services versus goods, Asian versus North American markets, competition in high-technology versus low-technology markets). They discuss the implications of these findings and offer directions for further research.