Sustainable supply chain management and the transition towards a circular economy: Evidence and some applications

In the last decades, green and sustainable supply chain management practices have been developed, trying to integrate environmental concerns into organisations by reducing unintended negative consequences on the environment of production and consumption processes. In parallel to this, the circular economy discourse has been propagated in the industrial ecology literature and practice. Circular economy pushes the frontiers of environmental sustainability by emphasising the idea of transforming products in such a way that there are workable relationships between ecological systems and economic growth. Therefore, circular economy is not just concerned with the reduction of the use of the environment as a sink for residuals but rather with the creation of self-sustaining production systems in which materials are used over and over again.Through two case studies from different process industries (chemical and food), this paper compares the performances of traditional and circular production systems across a range of indicators. Direct, indirect and total lifecycle emissions, waste recovered, virgin resources use, as well as carbon maps (which provide a holistic visibility of the entire supply chain) are presented. The paper asserts that an integration of circular economy principles within sustainable supply chain management can provide clear advantages from an environmental point view. Emerging supply chain management challenges and market dynamics are also highlighted and discussed.     

基于SVM的Web日志挖掘及潜在客户发现

潜在的客户资源是商家未来的利润来源,发现了潜在的客户就可以制定相应的商业决策,并进行有针对性的客户关系管理。使用SVM方法对Web日志文件进行挖掘,以发现站点访问者中潜在客户的共同行为模式,并将其分为不同级别的目标客户群。同时,通过试验4种不同比例的训练样本,研究了非对称数据对分类结果的影响,以期获得较优的模型。     

A decision support methodology for strategic planning in maritime transportation

This paper presents a decision support methodology for strategic planning in tramp and industrial shipping. The proposed methodology combines simulation and optimization, where a Monte Carlo simulation framework is built around an optimization-based decision support system for short-term routing and scheduling. The simulation proceeds by considering a series of short-term routing and scheduling problems using a rolling horizon principle where information is revealed as time goes by. The approach is flexible in the sense that it can easily be configured to provide decision support for a wide range of strategic planning problems, such as fleet size and mix problems, analysis of long-term contracts and contract terms. The methodology is tested on a real case for a major Norwegian shipping company. The methodology provided valuable decision support on important strategic planning problems for the shipping company.     

基于神经网络的期货套期保值决策支持系统

针对期货套期保值业务的特点 ,分析了期货套期保值决策支持系统的整体逻辑 ,尝试用人工神经网络专家系统预测期货行情走势 ,介绍了如何将期货市场与 BP网络有机结合起来构造适合期价预测的模型 ,并且在实证分析中给出了寻找最优预测效果的方法以及预测结论应用分析 .同时 ,提出了以此分析为基础的 DSS系统结构和功能 ,对辅助套期保值者决策有一定的指导意义     

群体会话支持系统的概念模型及应用

提出了一个群体会话支持系统的概念模型 ,并讨论了基于该模型的群件信息系统的构筑方法 .群体会话支持系统的概念模型可以用于不同的组织结构和不同的工作形态 .会话模式不仅是现实群体活动的抽象 ,同时也是构筑计算机的群体会话系统的理论依据 .系统设计人员可以根据离散的会话状态的数学表达 ,设计信息系统中的信息交互方式 ,根据信息系统的软、硬件配置可以比较容易地实现具体的任务 ,从而对基于计算机的群体会话活动提供有效的支持     

模型的事例表示

基于事例推理的模型管理系统中 ,有效地表达事例是实现系统的基础 .模型事例不是属性值事例 ,而是结构事例 .本文针对原有表达事例方式的不足提出了一种模型事例的表达方法 ,该方法适合于各种数值类模型的表示 ,并能够脱离模型的语义 ,同时给出了此种事例库组织的初步方案 ,为以后的研究奠定了基础 .     

Hard‐to‐Solve Bimatrix Games

The Lemke–Howson algorithm is the classical method for finding one Nash equilibrium of a bimatrix game. This paper presents a class of square bimatrix games for which this algorithm takes, even in the best case, an exponential number of steps in the dimension d of the game. Using polytope theory, the games are constructed using pairs of dual cyclic polytopes with 2d suitably labeled facets in d‐space. The construction is extended to nonsquare games where, in addition to exponentially long Lemke–Howson computations, finding an equilibrium by support enumeration takes on average exponential time.     

TEI@I方法论及其在外汇汇率预测中的应用

基于TE I@I方法论的理论框架,构建了一个基于TE I@I方法论的外汇汇率预测模型。在此模型中,传统的经济计量模型用于处理外汇汇率的主要趋势,人工神经网络技术用于分析外汇汇率的非线性,而文本挖掘和专家系统用于处理外汇市场中的突现性和不稳定性。最后,基于集成的思想,利用支持向量回归技术对上述3个部分进行非线性集成,从而获得一个更为精确的预测结果。通过实证方法验证了基于TE I@I方法论的外汇汇率预测模型的有效性。     

数据挖掘技术在CRM中的应用

客户关系管理(CRM)是数据挖掘技术的重要应用领域,也正是因为具有数据挖掘技术的支持才使CRM具有越来越广泛的市场价值和研究价值。本篇论文综述了面向CRM的数据挖掘应用的总体研究情况。包括面向CRM数据挖掘的体系结构;从客户生命周期的角度和行业应用角度分析了CRM中数据挖掘的应用状况;最后结合当前数据挖掘技术的发展指出了CRM中数据挖掘应用的进一步发展趋势以及我国在该领域的研究方向。     

The effects of JDC model on burnout and work engagement: A multiple interaction analysis

This study investigated the moderating effects of functional social support (emotional and instrumental support) on the relationship of job demand control with burnout and work engagement. In total, 297 frontline employees from a hotpot restaurant franchise in China were surveyed. The results indicated emotional support, such as caring and inspiration, mitigated the adverse effects of high demand/low control on burnout and work engagement. Instrumental support, such as giving suggestions and solving problems, only mitigated the adverse effects of burnout. Further, the high demand/low control/low emotional support work condition was the most unfavourable for work engagement and burnout; while high demand/low control/low instrumental support was the most unfavourable condition for burnout. The theoretical and managerial implications of this research have been provided to gain a deeper insight into functional social support in the job demand control model.