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"Too many Cooks Spoil the Broth": Key Persons and Their Roles in Inter-Organizational Innovations
(2013)
Key persons can play an important role in the development and diffusion of new products, processes or technologies. Their functions, contributions and interactions within companies have been subject to numerous investigations. From a theoretical point of view, promotor theory focuses on several specialists to overcome different barriers to innovation, while champion theory concentrates on generalists playing multiple roles. Empirical results point to generalists being better suited for highly innovative projects, but on the other hand different roles should preferably be played by different key persons. A central gap in the literature is that this issue has not been investigated sufficiently so far in an inter-organizational context. The questions are: Is role accumulation beneficial for innovation project performance with respect to the key persons? Is role accumulation even more advantageous with increasing degrees of innovativeness? A sample of 107 innovation projects where small and medium-sized enterprises take part is used as a unit of analysis. The network manager served as the respondent. A measurement approach based on an extended Rasch scale was introduced for this purpose. The results show that indeed ‘too many cooks spoil the broth’: Instead of many single-role players in each organization, we need a few multiple role players in an inter-organizational context.
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.
Analyzing Online Reviews to Measure Technology Acceptance at the Point of Scale: The Case of IKEA
(2015)
Increasingly, retailers rely on interactive technologies to improve consumers' shopping experiences. On the one side, interactive kiosks and smart mirrors make use of dedicated devices and software to explain, configure, and recommend products. On the other side, computer programs – so-called apps – are installed on the consumer's own device for the same purpose. They can be used at home, or – if installed on a mobile device – in retail outlets or on the move. In all cases, augmented reality (AR) can support these purposes by placing virtual content (e.g. newfurniture) in a real environment (the consumer's home). The overall perception and acceptance toward such interactive technologies are discussed in this paper. Users' perceptions and experiences are measured by applying a modified technology acceptance model (TAM). Four experiments, two with marker-based and two
with markerless AR apps are presented to support the generalization of the results, the measurement models
and the measurement approach. The results are satisfactory with regard to the robustness of the TAM model. However, the relative importance of hedonic (enjoyment, pleasure, fun) and utilitarian (information) aspects varies for different kinds of AR apps and has to be considered for improvement to occur. From a measurement point of view the acquiescence bias has to be dealt with when developing scale items.
Locational factors, like the quantity and quality of skilled labour, demanding customers, competitors, supporting industries, and research institutions, are assumed to have an influence on the competitiveness of a region and the performance of the regional actors. However, few studies focus on this topic from an innovation network perspective in the energy sector. Our study tries to close this gap: a sample of 128 German innovation networks of companies and research institutes in the energy sector is used to analyse the effects of locational factors on the performance (effectiveness) of innovation projects. Based on the distinctions in Porter’s Diamond Model, we find that two locational factors—the quality and quantity of the demand conditions and skilled labour—have positive effects. In contrast to the widespread assumption in the literature we could not find evidence for positive impacts on the quality and quantity of the competitive environment. In fact, the effect on performance was negative.
The analysis of the importance of supply side and demand side factors with regard to innovative behavior is quite old. In this paper, these two categories are used to distinguish
and examine the relevance of several success factors for collaborative innovation projects on the firm level in the German energy sector. The literature emphasizes that solving
environmental problems requires extensive technological change. On the other hand, due to higher prices the market push is weaker. Regulatory factors are therefore designed to
stimulate environmental innovations. The relative influence of these three categories on project performance is investigated on the basis of a sample of 128 German collaborative energy innovation projects in the development phase using a scale-based approach and structural equation modeling at the firm level. The results confirm the importance of supply side factors followed by demand side factors. In contrast to literary assumptions, R&D
subsidies played no significant role.
Die Paper werden begutachtet:
The goal of the review process is to select a number of papers that will stimulate discussion and the development of new knowledge, with preference given to empirical research. Some of the papers will inevitably be more fully developed than others; however, it is hoped that each author will gain insights during the conference that will strengthen their research and introduce them to other scholars who share their interests.
The review process examines over 300 submissions each year. Authors submit an extended abstract of about 500 words in length. This abstract should identify the central research question, introduce the most important references and describe the methodology, empirical base, analysis, and results. Each abstract is evaluated by two or three members of the scientific committee. All are senior professors who are well positioned internationally in the field. Each abstract is evaluated using the following points.
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.