Common Beliefs and Reality About PLS

This article addresses Rönkkö and Evermann’s criticisms of the partial least squares (PLS) approach to structural equation modeling. We contend that the alleged shortcomings of PLS are not due to problems with the technique, but instead to three problems with Rönkkö and Evermann’s study: (a) the adherence to the common factor model, (b) a very limited simulation designs, and (c) overstretched generalizations of their findings. Whereas Rönkkö and Evermann claim to be dispelling myths about PLS, they have in reality created new myths that we, in turn, debunk. By examining their claims, our article contributes to reestablishing a constructive discussion of the PLS method and its properties. We show that PLS does offer advantages for exploratory research and that it is a viable estimator for composite factor models. This can pose an interesting alternative if the common factor model does not hold. Therefore, we can conclude that PLS should continue to be used as an important statistical tool for management and organizational research, as well as other social science disciplines.

Linking Customer Knowledge With Successful Service Innovation

In order to satisfy customer needs and wants, the business-to-business service provider must develop and market services that provide value to the customers organization. Because of the importance and the difficulty of evaluating value from the customers perspective, a critical need exists for firms to obtain and possess knowledge about what activities create customer value for individual customers. The objective of this study is to explore the activities and knowledge needed to develop and market services that create customer value. Results of a study undertaken on the development and marketing of services and products in the telecommunications industry are provided. The report concludes with a discussion of managerial and research implications.

Examining the applicability of market forecasting models to new pharmaceutical products

Developing new products is a complex and risky business, particularly in the pharmaceutical industry. In recent years, several pretest and test market models have been proposed to evaluate the performance of a new product. Although these models have been tested and validated with a wide variety of frequently purchased products, certain unique characteristics of the market for pharmaceutical products render the models subject to modification. This study examines and evaluates the applicability of three types of market forecasting models (Awareness forecasting models, Pre-test market models, and Test market models) in predicting the market potential of new pharmaceutical products.

New drug adoption models: a review and assessment of future needs

New drug products today are the key to survival in the pharmaceutical industry. However, the new product development process in the pharmaceutical industry also happens to be one of the riskiest and most expensive undertakings because of the huge research and development costs involved. Consequently market forecasting of new pharmaceutical products takes on added importance if the formidable investments are to be recovered. New drug adoption models provide the marketer with a means to assess new product potential. Although several adoption models are available in the marketing literature for assessing potential of common consumer goods, the unique characteristics of the prescription drug market makes it necessary to examine the current state of pharmaceutical innovations. The purpose of this study, therefore, is to: (1) review new drug adoption models in the pharmaceutical literature, (2) evaluate the existing models of new drug adoption using the ten criteria for a good model as prescribed by Zaltman and Wallendorf (1983), and (3) provide an overall assessment and a ¿prescription¿ for better forecasting of new drug products.