Network learning: Episodes of interorganizational learning towards a collective performance goal

Little is known about learning processes in horizontal networks. This study focuses on networks as learning entities, i.e. learning by multiple organizations as a group, and the mechanisms involved in developing and addressing a network-level performance goal. By using a narrative approach, we gather in-depth primary data from network members to examine: how do firms engage in network learning? and, how is network learning coordinated towards a performance goal in a horizontal inter-firm network? Our findings comprise two learning episodes: ‘learning how to compete’ and ‘learning how to perform’. These episodes help us to understand network learning processes; the relationship between network learning and organizational learning; and the regulatory role a hub firm provides towards a collective performance goal.     

Universal versus contextual effects on TQM: a triangulation study using neural networks

The objective of this study is to extend previous research on total quality management (TQM)-context-performance relationships and ‘fit’ using multiple methods. We combine artificial neural networks (ANNs) with structural equation modelling (SEM) to analyse several hypotheses and propositions. This is the first study in this area of research that utilises ANNs and a triangulation technique in the presence of several contextual factors. The SEM analyses suggest that company size and industry type may have contingency effects on some of the TQM practices and/or TQM-performance relationships. However, the ANN models have shown that these two contingency factors do not moderate TQM outcomes, implying that all organisations can benefit from TQM regardless of size and type. As well, these models show that formal TQM implementation and/or ISO certifications do not add any predictive power to the ANN models except in one case: TQM implementation and/or ISO certification added to organisational effectiveness and customer results to predict financial and market (F&M) results. The results further indicate that even though implementing TQM alone has a bigger impact on F&M results than obtaining ISO certification alone, combining the two will have an even greater impact on these results. Joint implementation leads to greater improvements in organisational effectiveness, which, in turn, has a positive effect on customer results and consequently F&M results. This is a unique finding within the context of moderator effects on TQM-performance relationships.     

Connections and Constraints: The Effects of Children on Caregiving

This article assesses the effects of children on parents' involvement in caregiving. On the basis of interviews with 273 respondents, we address the effects of having children on care given to kin and nonkin; assess the effects of children's characteristics, especially age and gender, on the help mothers and fathers provide; and examine how these vary with mothers' employment. Overall, we find that the presence of children connects parents into networks of care more than it constrains them. The effects vary depending on the characteristics of the child (including age and gender) as well as characteristics of the parent (like gender and employment).     

Study of the behaviour of flexible production systems using neural nets

Owing to high development and acquisition costs, production systems require very detailed analysis for pre-design specifications, and an adjustment in operating philosophies. Detailed simulation models are one of the most important instruments to achieve this goal; normally the simulator must be custom-built, based on an accurate study of the specific industrial problem. The proposed management and economical analysis uses mathematical meta-models obtained from experimental designs produced by the simulator; today the detail level and precision required is very high, so these kinds of meta-model operate very close to their limit. Here we present a new methodology based on artificial neural networks that produces new types of meta-models which can correctly represent complex industrial systems. In this work we propose an application of this methodology together with a detailed analysis of the model development phase to highlight the potential of this instrument.     

Learning to negotiate network relations: social support among working mothers living in poverty

This study promotes our understanding of the complex and dynamic role that social support networks play in the everyday life of working mothers living in poverty, by focusing on the processes of negotiation involved in the creation, maintenance and mobilization of social ties. It is based on semi-structured interviews with 12 Israeli-Jewish working mothers who participated in an economic empowerment workshop. Findings indicate that the participants received much social support from relatives, friends and community activists. However, they further reveal the hard hidden work of negotiation and the process of learning involved in obtaining support. Particularly important in this context of poverty was the need to learn how to ask for support by overcoming feelings of shame and concerns about respectability, and to reduce social burdens by, among other things, refusing to participate in the ‘gift economy’ and limiting constraining social relationships. Finally, this study shows how the seemingly divergent interpretations of negotiation in social-exchange theory and symbolic interactionism (reaching an agreement that maximizes benefits versus preserving the relationship) often converge in everyday life situations.     

On the Nonlinear Predictability of Stock Returns Using Financial and Economic Variables

In a recent article by Qi, neural networks trained by Bayesian regularization were used to predict excess returns on the S&P 500. The article concluded that the switching portfolio based on the recursive neural-network forecasts generates higher accumulated wealth with lower risks than that based on linear regression. Unfortunately, attempts to replicate the results were unsuccessful. Replicated results using the same software, approach and data detailed by Qi indicate that, in fact, the switching portfolio based on the recursive neural-network forecasts generates lower accumulated wealth with higher risks than that based on linear regression.     

How to make e-Procurement viable for SME suppliers

Due to their common role as suppliers, small and medium-sized enterprises (SMEs) are especially challenged by today's turbulent business conditions. In order to meet this challenge, short-term WWW-based enterprise cooperations are regarded as an appropriate way to enhance the competitive strength of SMEs. Hence, the Institute of Machine Tools and Industrial Management (IWB) operates three so-called competence networks for engineering (www.engineering-net.de), rapid prototyping (www.rp-net.de) and manufacturing (www.produktionsnetz.de) services. For the purpose of an applied research project, more than 80 participating SME suppliers have been included in these specialized virtual markets, which are based on the core competencies of the cooperating SMEs. Additionally, the platform (www.virtueller-markt.de) enables customers to configure their specific supply chains via the above-mentioned competence networks. The presented paper depicts how to establish and operate these competence networks as well as how to configure supply chains via these virtual markets.     

Duality of departmental specializations and PhD exchange: A Weberian analysis of status in interaction using multilevel exponential random graph models (mERGM)

Weber proposes that lifestyle similarities preserve status by producing interactional closure between status similar actors. I investigate this theory on academic status hierarchies by conceptualizing sub-disciplinary specializations as departmental lifestyles and PhD exchange networks as interdepartmental interactions. Multilevel exponential random graph models (mERGM) reveal that the more specializations departments share, the more likely they are to exchange personnel. On the flip side, departments that do not share specializations are less likely to exchange doctoral candidates. Moreover, shared specializations are key determinants of closure between elite departments. These results support Weber’s theory and suggest that shared specializations preserve existing patterns of inequality between elite and non-elite departments.     

基于贝叶斯正则化的TDBPNN模型在中国外贸预报中的应用及评估

基于相空间重构的非线性预报思想,建立一个时滞的BP神经网络模型(TDBPNN),采用贝叶斯正则化方法提高BP网络的泛化能力,并将该模型应用于中国进出口贸易的预测,结果证明改进的TDBPNN模型具有较好的泛化能力,准确拟合了进出口贸易发展的历史值和趋势。区别于一般的预测评价,认为非线性预测不仅要注重数据拟合和精度改进,而且应该能够反映被预报系统的非线性特征。在分析模型预测精度的同时,通过计算拟合序列和原序列的非线性特征量进行模型评价,证实预测模型能够合理地“捕捉”到产生原序列的非线性系统的动力学特征。     

On Shortest k-Edge-Connected Steiner Networks in Metric Spaces

Given a set of points P in a metric space, let l(P) denote the ratio of lengths between the shortest k-edge-connected Steiner network and the shortest k-edge-connected spanning network on P, and let r = inf l(P) P for k 1. In this paper, we show that in any metric space, r 3/4 for k 2, and there exists a polynomial-time -approximation for the shortest k-edge-connected Steiner network, where = 2 for even k and = 2 + 4/(3k) for odd k. In the Euclidean plane, and .