Learning by exporting:lessons from high-technology SMEs

We investigate the learning by exporting hypothesis by examining the effect of exporting on the subsequent innovation performance of a sample of high-technology SMEs based in the UK. We find evidence of learning by exporting, but the pattern of this effect is complex. Exporting helps high-tech SMEs innovate subsequently, but does not make them more innovation intensive. There is evidence that consistent exposure to export markets helps firms overcome the innovation hurdle, but that there is a positive scale effect of exposure to export markets which allows innovative firms to sell more of their new-to-market products on entering export markets. Service sector firms are able to reap the benefits of exposure to export markets at an earlier (entry) stage of the internationalization process than are manufacturing firms. Innovation-intensive firms exhibit a different pattern of entry to and exit from export markets from low-intensity innovators, and this is reflected in different effects of exporting. © 2012 Elsevier Ltd.

Learning by exporting:lesson from high-technology SMEs

Theory points to the existence of a learning by exporting effect, in which exposure to export markets enhances performance through exposure to the knowledge stocks of trading partners. We investigate the learning by exporting hypothesis by examining the effect of exporting on the subsequent innovation performance of UK high-tech SMEs. We find evidence of learning by exporting, but the pattern of this effect is relatively complex. Exporting helps high-tech SMEs innovate subsequently, but does not make them more innovation intensive. There is also evidence that it is consistent exposure to export markets that helps firms overcome the innovation hurdle, but that there is a positive scale effect of exposure to export markets which allows innovative firms to sell more of their new-to-market products on entering export markets. Service sector firms are able to reap the benefits of exposure to export markets at an earlier (entry) stage of the internationalization process than are manufacturing firms. Firms producing a rapidly changing portfolio of innovative products exhibit higher churn in terms of entry to and exit from export markets than low-intensity innovators, and this is reflected in the effects of entry and exit into and out of such markets.

Network learning:an empirically-derived conceptual model of learning by groups of organizations

Building on a previous conceptual article, we present an empirically derived model of network learning - learning by a group of organizations as a group. Based on a qualitative, longitudinal, multiple-method empirical investigation, five episodes of network learning were identified. Treating each episode as a discrete analytic case, through cross-case comparison, a model of network learning is developed which reflects the common, critical features of the episodes. The model comprises three conceptual themes relating to learning outcomes, and three conceptual themes of learning process. Although closely related to conceptualizations that emphasize the social and political character of organizational learning, the model of network learning is derived from, and specifically for, more extensive networks in which relations among numerous actors may be arms-length or collaborative, and may be expected to change over time.

Network learning:Exploring learning by interorganizational networks

The importance of interorganizational networks in supporting or hindering the achievement of organizational objectives is now widely acknowledged. Network research is directed at understanding network processes and structures, and their impact upon performance. A key process is learning. The concepts of individual, group and organizational learning are long established. This article argues that learning might also usefully be regarded as occurring at a fourth system level, the interorganizational network. The concept of network learning - learning by a group of organizations as a group - is presented, and differentiated from other types of learning, notably interorganizational learning (learning in interorganizational contexts). Four cases of network learning are identified and analysed to provide insights into network learning processes and outcomes. It is proposed that 'network learning episode' offers a suitable unit of analysis for the empirical research needed to develop our understanding of this potentially important concept.

Foreign direct investment, technology sourcing and reverse spillovers

Recent theoretical work points to the possibility of foreign direct investment motivated not by 'ownership' advantages which may be exploited by a multinational enterprise but by the desire to access the superior technology of a host nation through direct investment. To be successful, technology sourcing foreign direct investment hinges crucially on the existence of domestic-to-foreign technological externalities within the host country. We test empirically for the existence of such 'reverse spillover' effects for a panel of UK manufacturing industries. The results demonstrate that technology generated by the domestic sector spills over to foreign multinational enterprises, but that this effect is restricted to relatively research and development intensive sectors. There is also evidence that these spillover effects are affected by the spatial concentration of industry, and that learning-by-doing effects are restricted to sectors in which technology sourcing is unlikely to be a motivating influence.

Growth expectations of business owners:impact of human capital, firm characteristics and environmental transition

This paper presents an empirical study based on a survey of 399 owners of small and medium size companies in Lithuania. Applying bivariate and ordered probit estimators, we investigate why some business owners expect their firms to expand, while others do not. Our main findings provide evidence that SME owner's generic and specific human capital matter. Those with higher education and 'learning by doing' attributes, either through previous job experience or additional entrepreneurial experience, expect their businesses to expand. The expectations of growth are positively related to exporting and non-monotonically to enterprise size. In addition, we analyse the link between the perceptions of constraints to business activities and growth expectations and find that the factors, which are perceived as main business barriers, are not necessary those which are associated with reduced growth expectations. In particular, perceptions of both corruption and of inadequate tax systems seem to affect growth expectations the most.

E-blogspot in the teaching of strategic management

E-learning and e-learning applications/tools are available to all educators thanks to the evolution of technology and the internet. Although a great variety of technologies are available it is not always obvious how these can be integrated in traditional teaching to support and enhance the learning experience. The majority of the existing literature proposes the use of blogging as an activity that students should do in order to increase their active participation in learning. This article presents the use of blogspots in the teaching of Strategic Management as a tool used to create greater linkages between theory and practice, discussing the evolution of its utilisation in my modules, the current state of use and a series of reflections on experience gained from its use so far. Overall, I have found that there is limited literature on how blogging could link to teaching activities and its utilisation should be viewed as learning by doing which is evaluated and improved by critical reflection of the user.

Supporting English language teachers doing further degrees at a distance:a web based strategy researched

This thesis explores how the world-wide-web can be used to support English language teachers doing further studies at a distance. The future of education worldwide is moving towards a requirement that we, as teacher educators, use the latest web technology not as a gambit, but as a viable tool to improve learning. By examining the literature on knowledge, teacher education and web training, a model of teacher knowledge development, along with statements of advice for web developers based upon the model are developed. Next, the applicability and viability of both the model and statements of advice are examined by developing a teacher support site (bttp://www. philseflsupport. com) according to these principles. The data collected from one focus group of users from sixteen different countries, all studying on the same distance Masters programme, is then analysed in depth. The outcomes from the research are threefold: A functioning website that is averaging around 15, 000 hits a month provides a professional contribution. An expanded model of teacher knowledge development that is based upon five theoretical principles that reflect the ever-expanding cyclical nature of teacher learning provides an academic contribution. A series of six statements of advice for developers of teacher support sites. These statements are grounded in the theoretical principles behind the model of teacher knowledge development and incorporate nine keys to effective web facilitation. Taken together, they provide a forward-looking contribution to the praxis of web supported teacher education, and thus to the potential dissemination of the research presented here. The research has succeeded in reducing the proliferation of terminology in teacher knowledge into a succinct model of teacher knowledge development. The model may now be used to further our understanding of how teachers learn and develop as other research builds upon the individual study here. NB: Appendix 4 is only available only available for consultation at Aston University Library with prior arrangement.

The evolution of learning systems:to Bayes or not to be

Bayesian algorithms pose a limit to the performance learning algorithms can achieve. Natural selection should guide the evolution of information processing systems towards those limits. What can we learn from this evolution and what properties do the intermediate stages have? While this question is too general to permit any answer, progress can be made by restricting the class of information processing systems under study. We present analytical and numerical results for the evolution of on-line algorithms for learning from examples for neural network classifiers, which might include or not a hidden layer. The analytical results are obtained by solving a variational problem to determine the learning algorithm that leads to maximum generalization ability. Simulations using evolutionary programming, for programs that implement learning algorithms, confirm and expand the results. The principal result is not just that the evolution is towards a Bayesian limit. Indeed it is essentially reached. In addition we find that evolution is driven by the discovery of useful structures or combinations of variables and operators. In different runs the temporal order of the discovery of such combinations is unique. The main result is that combinations that signal the surprise brought by an example arise always before combinations that serve to gauge the performance of the learning algorithm. This latter structures can be used to implement annealing schedules. The temporal ordering can be understood analytically as well by doing the functional optimization in restricted functional spaces. We also show that there is data suggesting that the appearance of these traits also follows the same temporal ordering in biological systems. © 2006 American Institute of Physics.

Learning in ultrametric committee machines

The problem of learning by examples in ultrametric committee machines (UCMs) is studied within the framework of statistical mechanics. Using the replica formalism we calculate the average generalization error in UCMs with L hidden layers and for a large enough number of units. In most of the regimes studied we find that the generalization error, as a function of the number of examples presented, develops a discontinuous drop at a critical value of the load parameter. We also find that when L>1 a number of teacher networks with the same number of hidden layers and different overlaps induce learning processes with the same critical points.

Social software in Higher Education:the diversity of applications and their contributions to students' learning experiences

Higher education institutions are increasingly using social software tools to support teaching and learning. Despite the fact that social software is often used in a social context, these applications can significantly contribute to the educational experience of a student. However, as the social software domain comprises a considerable diversity of tools, the respective tools can be expected to differ in the way they can contribute to teaching and learning. In this review on the educational use of social software, we systematically analyze and compare the diverse social software tools and identify their contributions to teaching and learning. By integrating established learning theory and the extant literature on the individual social software applications we seek to contribute to a theoretical foundation for social software use and the choice of tools. Case vignettes from several UK higher education institutions are used to illustrate the different applications of social software tools in teaching and learning.