New product development in German and US technology firms

Abstract

This research tested a model in both Germany and the USA that contained marketing variables known to impact new product development success in high technology firms. We explore the link between national culture and new product development. A multi‐group LISREL analysis revealed that while the model structure is valid for both countries, the impact of certain marketing factors on commercial product success differed. The analysis revealed that the mean values of the marketing factors differed significantly in each country. The most important determinant of new product success in both countries is proficiency in product launch activities. Marketing skills also positively impact product success in both countries. Top management support and involvement was also an important predictor of new product success in Germany, but the impact was negative. The potential impact of culture on the findings is discussed.

An Empirical Investigation of Architectural Heritage Management Implications for Tourism: The Case of Portugal

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Using BPNN and DEMATEL to modify importance–performance analysis model – A study of the computer industry

“…made use of partial correlation analysis to identify the hidden importance of quality characteristics. Simpson et al (2002) exploited structural equation modeling to calculate the mutual causal relationship among variables, and total impact coefficient (direct coefficient with indirect coefficient) as the variable importance. The importance of the quality characteristic is more favorable than the importance of self-expression, these statistical methods are given with three assumptions -constant, linear, and independent -that are different from actual scenario and they lead to erroneous results: Three separate steps are found in BPNN to evaluate hidden importance, and they are as follows:…”

“…For instance, Matzler and Sauerwein (2002) used multi-regression analysis to derive the relative importance of quality characteristics, termed as the hidden importance. Simpson, Kollmannsberger, Schmalen, and Berkowitz (2002) exploited structural equation modeling (SEM) to derive the relationship among quality characteristics, while the impact factor was used as the relative importance for quality f characteristic.…”