LS ABWL und Besondere des Marketing und des Innovationsmanagement
Open innovation and the integration of external sources have become increasingly important for the automotive industry. Users and customers possessing needs and problems are major sources for innovative ideas. The idea generation can be supported by the use of specific methods and instruments. This study investigates internal and external sources of innovative ideas and the use of voice-of-customer (VoC) methods in the German automotive industry. A special focus is on the lead user method which involves users who are ahead of the market making them attractive sources for innovative ideas. The findings show that easy to use VoC methods are mostly used to gather customer wants and needs. Nevertheless, more complex methods such as the lead user method proved advantageous with regard to the quality and quantity of innovative ideas. Because negative aspects became less important with increasing usage frequency, their usage should be encouraged.
Nowadays, the lead user method is a state of the art method used to generate breakthrough innovations for the new product development. Since the lead user method was successfully applied in generating simple products for business-to-business environments, the contribution of lead users in a complex product environment is highly controversial. This research adopts this to generate future complex IT-security solutions for business-to-business environments in the energy sector. The combined approach of lead user intelligence and voice of the customer techniques is expected to lower the risk of an unreliable product development and to fasten the lead user method. The empirical findings show an appropriate lead user method fitting small- and medium-sized enterprises (SMEs) restricted resources and requirements of effective research and development processes in a high-technology environment. It further enables SMEs to specify and parameterise future products according to reliable and user verified data within development processes.
Since its introduction into the marketing literature by Martilla and James, the Importance-Performance Analysis has proven multiple times to be a cost-effective technique for measuring attribute importance and performance of services for the customer. Additionally, it gives managers valuable hints in order to improve their products and services. However, despite a long list of successful applications overtime one critical aspect remains—the validation of the importance values by direct measurement. Besides the limitations and critics that accompanied with stated importance techniques, a lot of research results show that it is better to use direct methods in place of indirect measures. Some researchers suggest measuring the customers’ priority structure to compensate the critical points within the direct questioning. This study shows how the critical incident technique can be helpful for the validation of such results.
Online reviews by users have become an increasingly important source of information. This is true not only for new users of goods or services, but also for their producers. They extend the insight into the acceptance of new goods and services, e.g. at the point of sale, from a mere sales and usage quantity oriented point of view to a cause and effect oriented one. Since online reviews by consumers of many goods and services are nowadays widespread and easily available on the internet, the question arises whether their analysis can replace the more traditional approaches to measure technology acceptance, e.g., using questionnaires with TAM (Technology Acceptance Model) items. This paper tries to answer this question using IKEA's mobile catalogue app as an example. For comparisons reasons, data on the acceptance of the current version of this catalogue is collected in four different ways, (1) as answers to batteries of TAM items, (2) as assignments to pre-defined adjective pairs, (3) as textual likes and dislikes of users (simulating online reviews), and (4) as publicly available (real) reviews by users. The source for (1)–(3) is a survey with a sample of respondents, the source for (4) an online forum. The data is analyzed using partial least squares (PLS) for TAM modelling and text mining for pre-processing the textual data. The results are promising: it seems that data collection via surveys can be replaced – with some reservations – by the analysis of publicly available (real) online reviews.