Daniel Baier

Success Factors for Innovation Management in Networks of Small and Medium Enterprises

Because firms today operate in increasingly turbulent and complex environments, they need to be more proactive and innovative. Networks are gaining in importance, especially for small and medium enterprises with limited resources as R&D cooperations or cooperations along the value chain seem to be the only way to succeed with technologically challenging and promising but also expensive and risky product innovations. One of the key problems of these networks, however, is the question of how to plan, organize and control the innovation processes that are distributed over several partners. Theoretically derived and empirically proven success factors could help as much here as in the traditional success/failure discussion of new product development within firms. This paper discusses the effects of such factors, which partly derive from the traditional success/failure discussion within firms (e.g. market potential, product advantage, technological synergy, proficiency of technological or marketing activities) but also factors derived from recent network research (e.g. trust or dependence on partners). Their effect on new product performance is discussed on the basis of a comprehensive survey with 271 participating networks. The results confirm the traditional success factors, especially the product advantage and proficiency factors. But they also show that network-related success factors (especially network cohesion and organization) are of similar major importance.

Two-Mode Overlapping Clustering With Applications to Simultaneous Benefit Segmentation and Market Structuring

A new two-mode overlapping clustering procedure is presented. This procedure includes solution possibilities for two-mode (non-)overlapping additive clustering as well as (non-)overlapping clusterwise regression with conjoint experiments and can be used for simultaneous benefit segmentation and market structuring. Applications of various cases of the new procedure to conjoint data are used for comparisons.

Optimal product positioning based on paired comparison data

A new approach for analyzing paired comparison data is proposed which combines a probabilistic ideal point model with product positioning issues. Unlike traditional approaches based on paired comparison data the same formulation is used for estimating a joint space representation of consumer segments and products as well as for determining optimal (new) product positioning options in a relevant product-market. A Monte Carlo experiment is presented and real-world coffee market data are used to show advantages of the new approach.

Conjoint Analysis and Stimulus Presentation : a Comparison of Alternative Methods

The rapid development of the multimedia industry has led to improved possibilities to realistically present new product concepts to potential buyers even before prototypical realizations of the new products are available. Especially in conjoint studies — where product concepts are presented as stimuli with systematically varying features — the usage of pictures, sounds, animations, mock ups or even virtual reality should result in a reduction of respondent’s uncertainty with respect to (w.r.t.) innovative features and (hopefully) to an improved validity of the collected preferential responses. This paper examines differences between three different stimulus presentation methods: verbal, multimedia, and real.

Market Simulation Using a Probabilistic Ideal Vector Model for Conjoint Data

In commercial applications of conjoint analysis to product design and product pricing it has become quite popular to further evaluate the estimated individual part-worth functions by predicting shares of choices for alternatives in hypothetical market scenarios (Wittink, Vriens and Burhenne 1994 and Baier 1999 for surveys on commercial applications). Wide-spread software packages for conjoint analysis (Sawtooth Software’s 1994 ACA system) already include specific modules to handle this so-called market simulation situation for which, typically, a threefold input is required: (I) The (estimated) individual part-worth functions have to be provided. (II) A definition of a hypothetical market scenario is needed that allows to calculate individual utility values for each available alternative. (III) A so-called choice rule has to be selected, which relates individual utility values to expected individual choice probabilities and, consequently, to market shares for the alternatives. In this context, the determination of an adequate choice rule seems to be the most cumbersome task. Well-known traditional choice rules are, e.g., the 1ST CHOICE rule (where the individuals are assumed to always select the choice alternative with the highest utility value), the BTL (Bradley,Terry, Luce) rule (where individual choice probabilities are related to corresponding shares of utility values), and the LOGIT rule (where exponentiated utility values are used). Furthermore, in newer choice rules implemented by various software developers, the similarity of an alternative to other alternatives is taken into account as a corrective when choice probabilities are calculated (Sawtooth Software 1994).

‘Too Many Cooks Spoil the Broth’: Key Persons and Their Roles in Inter‐Organizational Innovations

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.

Methoden der Conjointanalyse in der Marktforschungs- und Marketingpraxis

Im vorliegenden Beitrag werden die wichtigsten methodischen Varianten der Conjointanalyse in Marktforschung und Marketing (die traditionelle, die hybride, die adaptive, und die auswahlbasierte Conjointanalyse) vorgestellt und uber ihren Einsatz in der Unternehmenspraxis berichtet. Die Untersuchung zur Verbreitung der Methoden stutzt sich dabei auf Erhebungen bei den wichtigsten kommerziellen Anbietern fur Conjointstudien in Deutschland.

Image Clustering for Marketing Purposes

Clustering algorithms are standard tools for marketing purposes. For example, in market segmentation, they are applied to derive homogeneous customer groups. However, recently, the available resources for this purpose have extended. So, e.g., in social networks potential customers provide images – and other information as e.g. profiles, contact lists, music or videos – which reflect their activities, interests, and opinions. Also, consumers are getting more and more accustomed to select or upload personal images during an online dialogue. In this paper we discuss, how the application of clustering algorithms to such uploaded image collections can be used for deriving market segments. Software prototypes are discussed and applied.

Erfassung von Kundenpräferenzen für Produkte und Dienstleistungen

Wenn neuartige Produkte oder Dienstleistungen im Markt zu positionieren sind, ist die Berucksichtigung der Kundenwunsche bei der Produkt- oder Dienstleistungsentwicklung unerlasslich. Hierfur ist es notwendig, besonders fruhzeitig und vor allem valide die Praferenzen der (spateren) Kunden zu ermitteln. Bei der Praferenz handelt es um einen eindimensionalen Indikator, mit dem das Ausmas der Vorziehenswurdigkeit eines Beurteilungsobjektes fur eine bestimmte Person wahrend eines bestimmten Zeitraumes zum Ausdruck gebracht wird. Die Conjointanalyse, als Standardmethode bei der Ermittlung von Praferenzen, versucht diese Praferenzen von Einzelpersonen oder Personenmehrheiten fur verschiedene Konzeptalternativen zu erklaren. Die analysierten Konzeptalternativen konnen sowohl Produkte als auch Dienstleistungen sein. Haufig handelt es sich dabei um Produkte oder Dienstleistungen, die in irgendeiner Art neuartig oder sogar innovativ sind – entweder fur den Kunden und/oder fur den Anbieter.

Image data analysis and classification in marketing

Nowadays, the diffusion of smartphones, tablet computers, and other multipurpose equipment with high-speed Internet access makes new data types available for data analysis and classification in marketing. So, e.g., it is now possible to collect images/snaps, music, or videos instead of ratings. With appropriate algorithms and software at hand, a marketing researcher could simply group or classify respondents according to the content of uploaded images/snaps, music, or videos. However, appropriate algorithms and software are sparsely known in marketing research up to now. The paper tries to close this gap. Algorithms and software from computer science are presented, adapted and applied to data analysis and classification in marketing. The new SPSS-like software package IMADAC is introduced.