基于GNNM(1.1)模型的货运量及货运周转量预测

通过各种算法对货运指标进行有效预测,对于把握未来货运发展趋势有着非常重要的作用。文章将灰色预测与神经网络预测方法进行了有机结合,建立了一个基于灰色神经网络的预测(GNNM)模型。通过模型对货运量及货运周转量进行了预测,得到了较满意的结果,表明了模型具有较高的可靠性及实用性。     

Neighbourhood Effects as Indirect Effects: Evidence from a Dutch Case Study on the Significance of Neighbourhood for Employment Trajectories

One of the key challenges in the study of neighbourhood effects on work is to understand the pathways through which disadvantaged neighbourhoods impact the employment opportunities of residents. Endogenous explanations for neighbourhood effects focus on social life in these neighbourhoods, identifying mechanisms of social isolation, deviant work ethics and neighbourhood disorder. This article studies these mechanisms in a low‐income neighbourhood in the Netherlands. The case study shows that unfavourable socioeconomic outcomes can be indirect and unintended consequences of actions and choices in everyday life that are not directly concerned with work. Nevertheless, these individual actions and choices reflect local social practices that are influenced by the marginalized context in which residents lead their lives.     

Advances in forecasting with neural networks? Empirical evidence from the NN3 competition on time series prediction

This paper reports the results of the NN3 competition, which is a replication of the M3 competition with an extension of the competition towards neural network (NN) and computational intelligence (CI) methods, in order to assess what progress has been made in the 10 years since the M3 competition. Two masked subsets of the M3 monthly industry data, containing 111 and 11 empirical time series respectively, were chosen, controlling for multiple data conditions of time series length (short/long), data patterns (seasonal/non-seasonal) and forecasting horizons (short/medium/long). The relative forecasting accuracy was assessed using the metrics from the M3, together with later extensions of scaled measures, and non-parametric statistical tests. The NN3 competition attracted 59 submissions from NN, CI and statistics, making it the largest CI competition on time series data. Its main findings include: (a) only one NN outperformed the damped trend using the sMAPE, but more contenders outperformed the AutomatANN of the M3; (b) ensembles of CI approaches performed very well, better than combinations of statistical methods; (c) a novel, complex statistical method outperformed all statistical and CI benchmarks; and (d) for the most difficult subset of short and seasonal series, a methodology employing echo state neural networks outperformed all others. The NN3 results highlight the ability of NN to handle complex data, including short and seasonal time series, beyond prior expectations, and thus identify multiple avenues for future research.     

基于BP神经网络的茶叶物流金融模式仿真优化

针对茶叶物流金融运作模式选择中的复杂性以及传统优化方法的局限性,将BP神经网络理论和仿真方法引入茶叶物流金融模式优化,考虑样本数量不足的实际问题,采用B样条函数插值方法扩充数据量,构建BP神经网络模型并加以训练。结果表明:BP神经网络具有精度较高的智能学习能力,适合于茶叶物流金融模式选择优化。     

Diffusion of environmental business practices: A network approach

The purpose of this research is to build a conceptual foundation that examines network effects on the diffusion of environmental business practices (EBP) among suppliers. This research extends a network perspective to adoption of an environmental business practice across a large network of suppliers. The context of EBP is used to better understand adoption of a complex business practice, with perceived costs that are often greater than the perceived benefit. Variation in the level of structural and relationship embeddedness affect network diffusion of environmental business practices differently. Increased levels of structural and relational embeddedness are proposed to be positively associated with diffusion of EBP. From a practical standpoint, firms that leverage embeddedness may facilitate higher diffusion and adoption of environmental business practices. This facilitation may lead network actors to engage in EBP, and leverage benefits that may stem from these practices. This research introduces the concept of embeddedness to the environmental supply chain literature. Practicing managers can use the findings in this research to better position themselves within a network to diffuse EBP. This research also helps managers understand how supply chain members that are weakly connected to the primary network are important for introducing new ideas and innovations.     

NOTES ON CONTRIBUTORS

Abstract

Within public administration and policy sciences the concept of policy networks nowadays is well accepted. Not much attention has been paid so far to strategies aimed at institutional design. Therefore, in this article, we develop a conceptual framework to study institutional design more thoroughly. We do this by specifying the nature and variety of institutional rules that guide the behaviour of actors within networks. Given this categorization of rules, we identify possible strategies to change network rules. Next, we focus on the strategic context of attempts to influence the nature of institutional rules: the process of institutional design. We conclude with suggestions to apply the conceptual framework to empirical research into the forms, impacts and implications of attempts to change the institutional features of policy networks.     

Pitfalls and Challenges for Trust and Effectiveness in Collaborative Networks

Abstract

Collaborative networks in the public and non-profit sector face challenges that are typical for their institutional context. The typical characteristics that might impede the functioning of networks and, in particular, the development of trust and network effectiveness, are related to type of instigation, network flexibility, and power in the form of unbalanced influence and the vertical character of networks. In a sample of 52 networks, the effects of network flexibility, mandatory and vertical networks, and influence on trust and network effectiveness were studied. Findings indicated that particularly flexibility in networks was important and that cognition-based trust played a central role in obtaining effective networks.     

Networks and linkages among firms and organizations in the Ottawa-region technology cluster

This paper reports on a study of the networking and linkage practices of technology and non-technology firms within the Ottawa cluster. The work seeks to understand how and why particular patterns of networks and linkages evolve and it examines empirically the usage and value of networks and linkages. Previous work argues that technology firms need to be relatively more adept at developing external relationships in order to be successful than do non-technology based companies. This work, however, finds that technology firms exhibit fewer linkages than non-technology based companies do within the Ottawa cluster. The research suggests that the vitality of the Ottawa cluster could be further enhanced through the promotion of additional networking and linkages among regional firms. A key implication for management practice is that CEOs of technology-based firms should work towards establishing and maintaining additional valued relationships.     

Developing a framework for network and cluster identification for use in economic development policy-making

Drawing on extensive academic research concerning clusters and networks, this paper seeks to create a framework capable of reviewing and monitoring different aspects of clusters and networks on an ongoing basis. The nine-element framework allows evaluation of the structures and processes for the eight basic cluster types identified from the literature. The use of this framework as a complimentary tool to the Multi-sectoral Qualitative Analysis (MSQA) methodology is then demonstrated using three examples (the construction, hardwood timber and higher education sectors). The data was gathered from three sets of key stakeholders (government, institutions and industry) provided from a recent study funded by the Welsh Assembly Government's Small Grants Research Programme. These cases illustrate the use of the framework in helping to generate the initial information necessary for subsequent cluster development policy (within overall regional economic development) by government to occur. The framework provides tools for reviewing and monitoring individual sectors. Information captured within the framework can also help in ameliorating problems in sectors likely to decline further. The need for further development research is also identified. Specifically at the level of the firm and network, there is a need to generate a more detailed framework of analysis of factors that contribute to successful processes of network management, learning and innovation, from which more detailed policy could be enacted in future.