Learning orientation and market orientation: From an alliance perspective

The literature on market orientation has grown in significance during the past decade. Whilst there is more literature on market orientation, the literature on learning orientation is also starting to increase. Numerous researchers have studied and found support for the positive relationship between market orientation and learning orientation (eg Slater and Narver 1995). However, not many researchers have investigated the relationship that firms with a high learning orientation have a high market orientation (eg Sinkula, Baker and Noordewier 1997). This paper attempts to investigate that link in more detail. An alliance perspective is taken in understanding this relationship.

Dual paths to performance: the impact of global pressures on MNC subsidiary conduct and performance

Over the last decade, the international business literature has placed ever-greater emphasis on the role that learning and innovation play in determining multinational and multinational subsidiary performance. The present research seeks to understand the organizational paths leading to such desirable outcomes as greater learning, increased innovation and improved performance. Using a model tested with data collected through a survey of managers in subsidiaries of multinational firms, we find dual, independent paths to improved performance - one through networking and inter-unit learning and the other through subsidiary autonomy and innovation. A particular feature of these findings is that they can be shown to be robust after controlling for a wide range of environmental pressures and firm and industry factors. However, in the absence of environmental controls the dual path finding is rejected. These conflicting findings support the imperative to test models that include a diverse range of environmental pressures so that the true effects of organizational factors on learning, innovation and performance can be identified.

Does industry matter? Examining the role of industry structure and organizational learning in innovation and brand performance

A manager's perception of industry structure (dynamism) has the potential to impact various organizational strategies and behaviors. This may be particularly so with regard to perceptions driving organizational learning orientations and innovation based marketing strategy. The position taken here suggests that firms operating within a competitive industry tend to pursue innovative ways of performing value-creating activities, which requires the development of learning capabilities. The results of a study of SMEs suggest that market focused learning, relative to other learning capabilities plays a key role in the relationships between industry structure, innovation and brand performance. The findings also show that market focused learning and internally focused learning influence innovation and that innovation influences a brand's performance. (c) 2005 Elsevier Inc. All rights reserved.

Orientation of biological cells using plane-polarized gaussian beam optical tweezers

Optical tweezers are widely used for the manipulation of cells and their internal structures. However, the degree of manipulation possible is limited by poor control over the orientation of the trapped cells. We show that it is possible to controllably align or rotate disc-shaped cells-chloroplasts of Spinacia oleracea-in a plane-polarized Gaussian beam trap, using optical torques resulting predominantly from circular polarization induced in the transmitted beam by the non-spherical shape of the cells.

Exploring the characteristics of the market-driven firms and antecedents to sustained competitive advantage

During the last few decades, identifying and examining the characteristics of market-driven firms have been a dominant theme in strategic marketing research. It has been argued that market-driven firms are superior in their market sensing and customer linking capabilities, enabling market-driven firms to outperform their competitors. This paper reports the findings of a study that examines the role market-focused learning capability and marketing capability in innovation-based competitive strategy on sustainable competitive advantage. The findings indicate that entrepreneurship is an important factor in sustained competitive advantage (SCA) and while market-focused learning capability leads to higher degrees of innovation, marketing capability enables SCA. (C) 2003 Elsevier Inc. All rights reserved.

Electricity market price spike forecast with data mining techniques

Electricity market price forecast is a changeling yet very important task for electricity market managers and participants. Due to the complexity and uncertainties in the power grid, electricity prices are highly volatile and normally carry with spikes. which may be (ens or even hundreds of times higher than the normal price. Such electricity spikes are very difficult to be predicted. So far. most of the research on electricity price forecast is based on the normal range electricity prices. This paper proposes a data mining based electricity price forecast framework, which can predict the normal price as well as the price spikes. The normal price can be, predicted by a previously proposed wavelet and neural network based forecast model, while the spikes are forecasted based on a data mining approach. This paper focuses on the spike prediction and explores the reasons for price spikes based on the measurement of a proposed composite supply-demand balance index (SDI) and relative demand index (RDI). These indices are able to reflect the relationship among electricity demand, electricity supply and electricity reserve capacity. The proposed model is based on a mining database including market clearing price, trading hour. electricity), demand, electricity supply and reserve. Bayesian classification and similarity searching techniques are used to mine the database to find out the internal relationships between electricity price spikes and these proposed. The mining results are used to form the price spike forecast model. This proposed model is able to generate forecasted price spike, level of spike and associated forecast confidence level. The model is tested with the Queensland electricity market data with promising results. Crown Copyright (C) 2004 Published by Elsevier B.V. All rights reserved.

A rough cluster analysis of shopping orientation data

This paper describes the application of a new technique, rough clustering, to the problem of market segmentation. Rough clustering produces different solutions to k-means analysis because of the possibility of multiple cluster membership of objects. Traditional clustering methods generate extensional descriptions of groups, that show which objects are members of each cluster. Clustering techniques based on rough sets theory generate intensional descriptions, which outline the main characteristics of each cluster. In this study, a rough cluster analysis was conducted on a sample of 437 responses from a larger study of the relationship between shopping orientation (the general predisposition of consumers toward the act of shopping) and intention to purchase products via the Internet. The cluster analysis was based on five measures of shopping orientation: enjoyment, personalization, convenience, loyalty, and price. The rough clusters obtained provide interpretations of different shopping orientations present in the data without the restriction of attempting to fit each object into only one segment. Such descriptions can be an aid to marketers attempting to identify potential segments of consumers.