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Institute
BTU
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.
Nowadays, the application of conjoint analysis for measuring customers’ preferences for goods and services is wide-spread in marketing. A sample of customers is confronted with fictive offers and asked for evaluations. From these responses part worths for attribute levels of the offers are estimated and used to develop an optimal design and pricing for an offer. However, especially in tourism, it can be observed that attribute importance not only differs between customers but also varies over a single customer’s usage situations and her/his mood. In this paper, we propose a measurement approach that respects this variation. Part worths are stochastically modeled and estimated using Bayesian procedures. The approach is applied to design and price a water park.
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.
Marktsegmentierung
(2008)
There are many different approaches to measure dissimilarities between images on the basis of color
histograms. Some of them operate fast but generate results in contradiction to human perception. Others
yield better results, especially the Earth Mover’s Distance (EMD) (Rubner et al., Int J Comput Vis,
40(2):99–121, 2000), but its computational complexity prevents its usage in large databases (Ling et
al., IEEE Trans Pattern Anal Mach Intell, 29(5):840–853, 2007). This paper presents a new intuitive
intelligible approximation of EMD. The empirical study tries to answer the question whether the good
results of EMD justify its long computation time. We tested several distances with images that were
changed by normally-distributed failures and evaluate their results by means of the adjusted Rand index
(Hubert et al., J Classif, 2:193–218, 1985).